from google.colab import drive
drive.mount('/content/drive')
%cd /content/drive/MyDrive/HW2

Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount("/content/drive", force_remount=True).
/content/drive/MyDrive/HW2

RQ 1: Exploratory Data Analysis

We import the necessary libraries and set the dataset paths.

import pandas as pd
import json
import numpy as np
import matplotlib.pyplot as plt
import datetime

authors_set = 'lighter_authors.json'
books_set = 'lighter_books.json'

Loading the Authors Dataset

# Chunk size
chunk_size = 50000
# Initialize an empty list to store chunks
authors = pd.DataFrame()
# Loop through each chunk and append it to the result dataframe
for chunk in pd.read_json(authors_set, lines=True, chunksize=chunk_size):
    # Select only the required columns from the chunk
    #selected_chunk = chunk[["name", "gender", "fans_count", "average_rating", "ratings_count", "text_reviews_count", "works_count"]]
    # Append the selected chunk to the list
    authors = pd.concat([authors, chunk], ignore_index=True)

authors.head(5)

	ratings_count	average_rating	text_reviews_count	work_ids	book_ids	works_count	id	name	gender	image_url	about	fans_count
0	2862064	4.19	62681	[3078186, 135328, 1877624, 74123, 3078120, 104...	[386162, 13, 8695, 8694, 6091075, 365, 569429,...	106	4	Douglas Adams	male	https://images.gr-assets.com/authors/159137433...	Douglas Noël Adams was an English author, comi...	19826
1	1417316	4.02	84176	[613469, 2305997, 940892, 2611786, 7800569, 31...	[9791, 21, 28, 24, 7507825, 27, 10538, 25, 26,...	75	7	Bill Bryson	male	https://images.gr-assets.com/authors/157859752...	William McGuire "Bill" Bryson, OBE, FRS was bo...	16144
2	56159	4.53	352	[17150, 808427, 20487307, 90550, 25460625, 171...	[349254, 15222, 14833682, 15221, 18126815, 152...	14	10	Jude Fisher	female	https://images.gr-assets.com/authors/141145711...	Jude Fisher is the pseudonym for <a href="http...	60
3	3302	3.79	480	[4417, 14300808, 14780, 3796968, 44703121, 103...	[40, 9416484, 12482, 3753106, 26889789, 104764...	45	12	James Hamilton-Paterson	male	https://images.gr-assets.com/authors/127051738...	James Hamilton-Paterson's work has been transl...	72
4	7979	3.60	772	[13330815, 19109351, 42306244, 72694240, 26291...	[8466327, 15739968, 22756778, 51026133, 260451...	61	14	Mark Watson	male	https://images.gr-assets.com/authors/133175379...	Mark Andrew Watson (born 13 February 1980) is ...	179

authors.describe()

	ratings_count	average_rating	text_reviews_count	works_count	id	fans_count
count	3.517670e+05	351767.000000	351767.000000	3.517670e+05	3.517670e+05	351767.000000
mean	4.770586e+03	3.651194	330.993243	2.593714e+01	7.751861e+06	111.615731
std	9.769395e+04	1.211482	3857.539191	3.066083e+03	6.578409e+06	2661.018139
min	-4.100000e+01	-31.000000	0.000000	0.000000e+00	4.000000e+00	-33.000000
25%	6.000000e+00	3.600000	1.000000	2.000000e+00	1.535315e+06	1.000000
50%	3.900000e+01	3.950000	8.000000	6.000000e+00	6.470396e+06	4.000000
75%	3.100000e+02	4.250000	53.000000	1.500000e+01	1.434041e+07	20.000000
max	2.700375e+07	5.000000	608956.000000	1.775176e+06	2.124802e+07	766035.000000

Data Cleaning on Authors

authors2 = authors

authors2.shape

(351767, 12)

authors[authors.apply(lambda x: len(x.work_ids)!=x.works_count, axis=1)].shape[0]

444

These 444 rows are junk rows because count of work does not match with the number of work ids listed. Hence we will discard these rows.

authors2=authors2[authors2.apply(lambda x: len(x.work_ids)==x.works_count, axis=1)]

authors2.describe()

	ratings_count	average_rating	text_reviews_count	works_count	id	fans_count
count	3.513230e+05	351323.000000	351323.000000	351323.000000	3.513230e+05	351323.000000
mean	4.484867e+03	3.650981	320.351201	16.279185	7.758528e+06	107.322885
std	9.136027e+04	1.211959	3641.125698	40.387565	6.578301e+06	2319.479591
min	-4.100000e+01	-31.000000	0.000000	0.000000	4.000000e+00	-33.000000
25%	6.000000e+00	3.600000	1.000000	2.000000	1.547222e+06	1.000000
50%	3.900000e+01	3.950000	8.000000	6.000000	6.471876e+06	4.000000
75%	3.080000e+02	4.250000	52.000000	15.000000	1.434526e+07	20.000000
max	2.700375e+07	5.000000	606373.000000	1511.000000	2.124802e+07	455358.000000

Looking at the negative minimum values of the numeric columns in this description, we decide to filter those out.

authors2.dropna(inplace=True)

<ipython-input-8-26e85020d60f>:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  authors2.dropna(inplace=True)

authors2 = authors2[(authors2[["fans_count", "average_rating", "ratings_count", "text_reviews_count", "works_count"]] >= 0).all(axis=1)]

authors2.describe()

	ratings_count	average_rating	text_reviews_count	works_count	id	fans_count
count	3.512960e+05	351296.000000	351296.000000	351296.000000	3.512960e+05	351296.000000
mean	4.485211e+03	3.651070	320.375586	16.280052	7.758450e+06	107.331498
std	9.136377e+04	1.210561	3641.264559	40.388956	6.578473e+06	2319.568516
min	0.000000e+00	0.000000	0.000000	0.000000	4.000000e+00	0.000000
25%	6.000000e+00	3.600000	1.000000	2.000000	1.546958e+06	1.000000
50%	3.900000e+01	3.950000	8.000000	6.000000	6.471733e+06	4.000000
75%	3.080000e+02	4.250000	52.000000	15.000000	1.434546e+07	20.000000
max	2.700375e+07	5.000000	606373.000000	1511.000000	2.124802e+07	455358.000000

Now the description gives proper values for the minimum of the numeric columns.

min(authors2['work_ids'])

[]

The minimum of the work_ids column has returned empty list, we will clear this junk as well and we repeat this same technique for all other non numeric columns.

authors2=authors2[authors2.apply(lambda x: x.work_ids!=[] and x.book_ids!=[],axis=1)]

authors2[authors2['gender']==''].shape[0]

103237

As per this query, I got 103237 rows with no Gender of the author specified. To do a better analysis of the data, I am discarding these rows with no gender specified and saving it to another copy as authors3.

authors3=authors2[authors2['gender']!='']

authors3.shape[0]

248056

Loading the Books Dataset

# Chunk size
chunk_size = 50000
# Initialize an empty list to store chunks
books = pd.DataFrame()
# Loop through each chunk and append it to the result dataframe
for chunk in pd.read_json(books_set, lines=True, chunksize=chunk_size):
    # Select only the required columns from the chunk
    selected_chunk = chunk[["title", "num_pages", "language", "average_rating", "ratings_count","text_reviews_count", "author_name", "original_publication_date", "publication_date","format","series_id","series_name","series_position"]]
    #selected_chunk = chunk[["original_publication_date"]]
    # Append the selected chunk to the list
    books = pd.concat([books, selected_chunk], ignore_index=True)

books.head(5)

	title	num_pages	language	average_rating	ratings_count	text_reviews_count	author_name	original_publication_date	publication_date	format	series_id	series_name	series_position
0	Harry Potter and the Order of the Phoenix (Har...	870	eng	4.50	2628006	44716	J.K. Rowling	2003-06-21	2004-09	Paperback	45175	Harry Potter	5
1	Harry Potter and the Sorcerer's Stone (Harry P...	309	eng	4.48	7377351	116930	J.K. Rowling	1997-06-26	2003-11-01	Hardcover	45175	Harry Potter	1
2	Harry Potter and the Chamber of Secrets (Harry...	352	eng	4.43	2855044	55286	J.K. Rowling	1998-07-02	2003-11-01	Hardcover	45175	Harry Potter	2
3	Harry Potter and the Prisoner of Azkaban (Harr...	435	eng	4.57	2946694	58023	J.K. Rowling	1999-07-08	2004-05-01	Mass Market Paperback	45175	Harry Potter	3
4	Harry Potter and the Goblet of Fire (Harry Pot...	734	eng	4.56	2705676	48637	J.K. Rowling	2000-07-08	2002-09-28	Paperback	45175	Harry Potter	4

books.describe()

	average_rating	ratings_count	text_reviews_count
count	7.027431e+06	7.027431e+06	7.027431e+06
mean	3.306188e+00	1.945861e+04	6.417258e+02
std	1.435734e+00	1.609008e+05	4.169806e+03
min	0.000000e+00	0.000000e+00	0.000000e+00
25%	3.360000e+00	3.000000e+00	0.000000e+00
50%	3.810000e+00	4.500000e+01	5.000000e+00
75%	4.080000e+00	7.710000e+02	6.400000e+01
max	5.000000e+00	7.400639e+06	1.745240e+05

Data Cleaning on books:

books2 = books

books2.dropna(subset=["title", "num_pages", "language", "average_rating", "ratings_count", "author_name", "original_publication_date", "publication_date","text_reviews_count","format","series_id","series_name","series_position"], inplace=True)

books2.shape[0]

7027431

min(books2['title'])

''

I can see blank Title in the books dataset, I will discard such rows and apply the same technique to other columns.

books2= books2[books2.apply(lambda x: x.title!='' and x.author_name!='', axis=1)]

books2.shape[0]

7027398

# Filter out rows with incorrect values in "num_pages" (e.g., non-numeric values)
books2['num_pages'] = pd.to_numeric(books2['num_pages'], errors='coerce')
books2 = books2[books2['num_pages'].notna()]
books2 = books2[books2['num_pages'] != 0]
min_num_pages = books2["num_pages"].min()

<ipython-input-19-337f7037a939>:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books2['num_pages'] = pd.to_numeric(books2['num_pages'], errors='coerce')

books2 = books2[(books2[["average_rating", "ratings_count", "num_pages","text_reviews_count"]] >= 0).all(axis=1)]

from datetime import datetime

books2["original_publication_date"] = pd.to_datetime(books2["original_publication_date"], errors='coerce')
books2["original_publication_date"] = pd.to_datetime(books2["original_publication_date"])
present_date = datetime.now()
books2 = books2[books2['original_publication_date'] <= present_date]
books2["original_publication_date"].max()

Timestamp('2023-10-14 00:00:00')

books2 = books2[books2["author_name"] != "NOT A BOOK"]

books2 = books2[books2["language"] != ""]

books2 = books2.drop_duplicates(subset = ["title"])

books2.shape[0]

1271100

Exploratory Data Analysis on Authors set:

media = authors3['average_rating'].mean()
mediana = authors3['average_rating'].median()
minimo = authors3['average_rating'].min()
massimo = authors3['average_rating'].max()

print("Base statistics on average_rating")
print("mean", round(media, 2))
print("median", mediana)
print("min and max", minimo, massimo)

plt.boxplot(authors2["average_rating"], showfliers=True, patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2})
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of average_rating")
plt.show

Base statistics on average_rating
mean 3.71
median 3.95
min and max 0.0 5.0

<function matplotlib.pyplot.show(close=None, block=None)>

media = authors3['fans_count'].mean()
mediana = authors3['fans_count'].median()
minimo = authors3['fans_count'].min()
massimo = authors3['fans_count'].max()

print("Base statistics on fans_count")
print("mean", round(media, 2))
print("median", mediana)
print("min and max", minimo, massimo)

plt.boxplot(authors2["fans_count"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of fans_count")
plt.show

Base statistics on fans_count
mean 127.33
median 5.0
min and max 0 455358

<function matplotlib.pyplot.show(close=None, block=None)>

media = authors3['ratings_count'].mean()
mediana = authors3['ratings_count'].median()
minimo = authors3['ratings_count'].min()
massimo = authors3['ratings_count'].max()

print("Base statistics on ratings_count")
print("mean", round(media, 2))
print("median", mediana)
print("min and max", minimo, massimo)

plt.boxplot(authors2["ratings_count"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of fans_count")
plt.show

Base statistics on ratings_count
mean 5474.95
median 51.0
min and max 0 27003752

<function matplotlib.pyplot.show(close=None, block=None)>

conteggio_output = authors3['gender'].value_counts().reset_index()
conteggio_output.columns = ['gender', 'count']
conteggio_output_ordinato = conteggio_output.sort_values(by='count', ascending=False)
conteggio_output_ordinato = conteggio_output_ordinato[conteggio_output_ordinato["gender"] != ""]
maschifemmine = conteggio_output_ordinato[conteggio_output_ordinato["gender"].isin(["male", "female"])]
riga_altro = pd.DataFrame({"gender": ["other"], "count": [conteggio_output_ordinato["count"].sum() - maschifemmine["count"].sum()]})
maschifemmine = pd.concat([maschifemmine, riga_altro], ignore_index=True)
plt.figure(figsize=(6, 6))
plt.pie(maschifemmine['count'], labels=maschifemmine['gender'], autopct='%1.1f%%', colors=['lightblue', 'lightgreen', 'lightcoral'], startangle=140)
plt.title('')
plt.axis('equal')
plt.show()

Exploratory Data Analysis on Books Set

media = books2['num_pages'].mean()
mediana = books2['num_pages'].median()
minimo = books2['num_pages'].min()
massimo = books2['num_pages'].max()

print("Base statistics on num_pages")
print("mean", round(media, 1))
print("median", mediana)
print("min and max", minimo, massimo)

plt.boxplot(books2["num_pages"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of num_pages")
plt.show

Base statistics on num_pages
mean 3649.7
median 239.0
min and max 1.0 2147483647.0

<function matplotlib.pyplot.show(close=None, block=None)>

media = books2['average_rating'].mean()
mediana = books2['average_rating'].median()
minimo = books2['average_rating'].min()
massimo = books2['average_rating'].max()

print("Base statistics on average_rating")
print("mean", round(media, 2))
print("median", round(mediana, 2))
print("min and max", minimo, massimo)

plt.boxplot(books2["average_rating"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of average_rating")
plt.show

Base statistics on average_rating
mean 3.7
median 3.88
min and max 0.0 5.0

<function matplotlib.pyplot.show(close=None, block=None)>

media = books2['ratings_count'].mean()
mediana = books2['ratings_count'].median()
minimo = books2['ratings_count'].min()
massimo = books2['ratings_count'].max()

print("Base statistics on ratings_count")
print("mean", round(media, 2))
print("median", round(mediana, 2))
print("min and max", minimo, massimo)

plt.boxplot(books2["ratings_count"], patch_artist=True, boxprops={'facecolor': 'lightblue', 'linestyle': '--', 'linewidth': 2}, showfliers=True)
plt.grid(axis='y', linestyle='--', alpha=0.7)
plt.title("Box-plot of ratings_count")
plt.show

Base statistics on ratings_count
mean 19652.52
median 117.0
min and max 0 7400639

<function matplotlib.pyplot.show(close=None, block=None)>

books2["original_publication_date"] = pd.to_datetime(books2["original_publication_date"], errors='coerce')

books2["original_publication_date"] = pd.to_datetime(books2["original_publication_date"])

# Trova la data minima
data_minima = books2["original_publication_date"].min()

# Trova la data massima
data_massima = books2["original_publication_date"].max()

# Stampa i risultati
print("Minimum Date:", data_minima)
print("Maximum Date:", data_massima)

Minimum Date: 1678-01-01 00:00:00
Maximum Date: 2023-10-14 00:00:00

conteggio_output = books2['language'].value_counts().reset_index()
conteggio_output.columns = ['language', 'count']
conteggio_output = conteggio_output.dropna()  # Rimuovo le righe con valori mancanti
conteggio_output_ordinato = conteggio_output.sort_values(by='count', ascending=False)
print(conteggio_output_ordinato.head(10))

primi10 = conteggio_output_ordinato.head(10)
plt.bar(primi10["language"], primi10['count'])
plt.xlabel('Languages')
plt.ylabel('Count')
plt.show()

  language   count
0      eng  520345
1      spa   69574
2      ger   69184
3      ita   66776
4      fre   61948
5      por   49079
6    en-US   41403
7       nl   39031
8      ara   30207
9    en-GB   28752

del authors
del books

RQ 2: Retrieving some vital information:

Plot the number of books for each author in descending order.

author_book_counts = books2.groupby('author_name')['title'].count().reset_index()
author_book_counts = author_book_counts.sort_values(by='title', ascending=False)

# author names and book counts for top 50 authors
plt.figure(figsize=(12, 6))
plt.bar(author_book_counts[:50]['author_name'], author_book_counts[:50]['title'])
plt.xticks(rotation=90)
plt.xlabel('Author Name')
plt.ylabel('Number of Books')
plt.title('Number of Books for Top 50 Authors')
plt.show()

Which book has the highest number of reviews?

books2_sorted = books2.sort_values(by='text_reviews_count', ascending=False)
print(f"The book with the highest number of text reviews is '{books2_sorted['title'][1]}' with {books2_sorted['text_reviews_count'][1]} reviews.")

The book with the highest number of text reviews is 'Harry Potter and the Sorcerer's Stone (Harry Potter, #1)' with 116930 reviews.

Which are the top ten and ten worst books concerning the average score?

# Sort books by average rating in descending order for the top ten
best_books = books2.sort_values(by='average_rating', ascending=False)
ten_best_books= best_books.head(10)[['title','average_rating']]
# Sort books by average rating in ascending order for the ten worst
worst_books = books2.sort_values(by='average_rating', ascending=True)
ten_worst_books= worst_books.head(10)[['title','average_rating']]
# Print the top ten and ten worst books
print("Top Ten Books with Highest Average Rating:\n")
print(ten_best_books)
print("\nTen Worst Books with Lowest Average Rating:\n")
print(ten_worst_books)

Top Ten Books with Highest Average Rating:

                                                     title  average_rating
3355748  The Gospel of Matthew/The Death of Ivan Ilych/...             5.0
4684994                                Gigia ha il Diabete             5.0
6256490                   Now Is Not The Time For Trumpets             5.0
4685312  Whiz Tanner and the Vanishing Diamond (Tanner-...             5.0
4685142                      My Favourite Children's Songs             5.0
4685124                         The World Is a Scary Place             5.0
3472547                             Soulis Joe's Lost Mine             5.0
3472552                             Dissecting Sean Connor             5.0
3472556                                A Spoonful of Sugar             5.0
3472582                                      Бог в Ню Йорк             5.0

Ten Worst Books with Lowest Average Rating:

                                                     title  average_rating
4414879                     Lionne; Or the Doom of Deville             0.0
3100783         Cómo conocer los instrumentos de orquesta             0.0
2238885                    The Changing Face Of Warminster             0.0
844390   Spectacular Wineries of Napa Valley: A Captiva...             0.0
5540582  Risk Management: Gestão, Relato e Auditoria do...             0.0
4697326                                    Wagner's Heroes             0.0
844237          La conspiración. El golpe de estado difuso             0.0
4697334  Segovia. Pueblo, ciudad y tierra. Horizonte hi...             0.0
3100920                     De la connaissance de soi-même             0.0
6799524                             Youth Worship and Sing             0.0

Explore the different languages in the book’s dataset, providing a proper chart summarizing how these languages are distributed throughout our virtual library.

lang_counts = books2['language'].value_counts().reset_index()
lang_counts.columns = ['language', 'count']  # Correggi l'assegnazione delle colonne
(lang_counts.shape[0])

top50lang = lang_counts.head(50)
(top50lang.head(2))

top10lang = lang_counts[lang_counts["language"].isin(["eng", "ger", "spa", "fre", "ita", "en-US", "por", "en-GB", "nl", "ara"])]
(top10lang.head(10))

riga_altro = pd.DataFrame({"language": ["other 244 languages"], "count": [lang_counts["count"].sum() - top10lang["count"].sum()]})
top10lang = pd.concat([top10lang, riga_altro], ignore_index=True)

plt.figure(figsize=(8, 8))  # Imposta le dimensioni del grafico
plt.pie(top10lang['count'], labels=top10lang['language'], autopct='%1.1f%%', colors=['blue', 'green', 'red', 'yellow', 'orange', 'purple', 'pink', 'lightblue', 'brown', 'gray', 'cyan'], startangle=140)
plt.title('')
plt.axis('equal')
plt.show()

plt.hist(lang_counts['count'], bins=50, edgecolor='k')
plt.xlabel('Number of books')
plt.ylabel('Number of languages')
plt.title('Distribution of number of books per languages')
plt.show()

How many books have more than 250 pages?

books250more = books2[(books2[["num_pages"]] > 250).all(axis=1)]

print(f'Number of books with more than 250 pages is {books250more.shape[0]}')

Number of books with more than 250 pages is 597073

Plot the distribution of the fans count for the 50 most prolific authors (the ones who have written more books).

top50author = author_book_counts.head(50)
top50author = top50author.rename(columns={"author_name": "name"})

merged_df = pd.merge(top50author, authors3, on='name', how='left')

merged_df[["name","fans_count"]].head(5)

	name	fans_count
0	Various	NaN
1	Agatha Christie	NaN
2	Anonymous	NaN
3	Walt Disney Company	NaN
4	Enid Blyton	NaN

Appearance of NaN values. So I will drop them.

merged_df.dropna(subset=['fans_count'],inplace=True)

merged_df[["name","fans_count"]].head(5)

	name	fans_count
5	Nora Roberts	41402.0
13	Terry Pratchett	35674.0
15	J.R.R. Tolkien	59406.0
19	Rumiko Takahashi	1395.0
20	CLAMP	2630.0

# Plot the distribution of fans count
plt.figure(figsize=(8, 4))
plt.hist(merged_df['fans_count'], bins=50, edgecolor='k')
plt.xlabel('Fans Count')
plt.ylabel('Number of Authors')
plt.title('Distribution of Fans Count for the 50 Most Prolific Authors')
plt.show()

plt.figure(figsize=(8, 3))
plt.bar(merged_df['name'], merged_df['fans_count']/30000) #i have normalized the count
plt.xticks(rotation=90)
plt.xlabel('Author Name')
plt.ylabel('Fans Count')
plt.title('Fans Count for Top 50 Prolific Authors')
plt.show()

plt.figure(figsize=(6, 3))
plt.boxplot(merged_df['fans_count'], vert=False)
plt.xlabel('Fans Count')
plt.title('Distribution of Fans Count for the 50 Most Prolific Authors (Box Plot)')
plt.show()

RQ 3: Historical look at the dataset!

data sets loaded and cleaned previously as: authors3, books2

books2["original_publication_date"].min()

Timestamp('1678-01-01 00:00:00')

books2["original_publication_date"].max()

Timestamp('2023-10-14 00:00:00')

Write a function that takes as input a year and returns as output the following information:

The number of books published that year.

The total number of pages written that year.

The most prolific month of that year.

The longest book written that year.

def books_info_for_year(year):

    books_in_year = books2[books2['original_publication_date'].dt.year == year]

    # total number of books published in the given year
    Num_Books = len(books_in_year)

    # total number of pages written in the given year
    Total_Pages = books_in_year.loc[:,'num_pages'].sum()

    # to count the most prolific month
    #books_in_year['publication_month'] = books_in_year['original_publication_date'].dt.month
    books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month

    Most_Prolific_Month = None
    longest_book = None

    if not books_in_year.empty:
        # to find the most prolific month
        #books_in_year['month'] = books_in_year['original_publication_date'].dt.month
        books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
        Most_Prolific_Month = books_in_year['month'].value_counts().idxmax()

        # the longest book written in that year
        longest_book = books_in_year[books_in_year['num_pages'] == books_in_year['num_pages'].max()]['title'].values[0]



    return Num_Books, Total_Pages, Most_Prolific_Month, longest_book

import time
year = 2003
start_time=time.time()
result = books_info_for_year(year)
end_time=time.time()
print(result)
print(f"Time taken: {end_time - start_time:.2f} seconds")

(27855, 7902848.0, 1, 'Soldadura, Nivel Duo Guía del estudiante')
Time taken: 0.09 seconds

<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month

Use this function to build your data frame: the primary key will be a year, and the required information will be the attributes within the row. Finally, show the head and the tail of this new data frame considering the first ten years registered and the last ten years.

years = books2['original_publication_date'].dt.year.unique()
yearly_info = pd.DataFrame(columns=['Year', 'Num_Books', 'Total_Pages', 'Most_Prolific_Month', 'Longest_Book'])
start_time=time.time()
for year in years:
  Num_Books, Total_Pages, Most_Prolific_Month, Longest_Book = books_info_for_year(year)
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)

end_time=time.time()

<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)
<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)

Time taken to load DF: 22.99 seconds

<ipython-input-187-9faa3a9fad87>:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['publication_month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-187-9faa3a9fad87>:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  books_in_year['month'] = books_in_year.loc[:,'original_publication_date'].dt.month
<ipython-input-191-ed46fe91a165>:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  yearly_info = yearly_info.append({'Year': year, 'Num_Books': Num_Books, 'Total_Pages': Total_Pages, 'Most_Prolific_Month': Most_Prolific_Month, 'Longest_Book': Longest_Book}, ignore_index=True)

print(f"Time taken to load DF: {end_time - start_time:.2f} seconds")

Time taken to load DF: 22.99 seconds

print(yearly_info.head(10))

   Year Num_Books  Total_Pages Most_Prolific_Month  \
0  2003     27855    7902848.0                   1   
1  1997     19107    5390938.0                   1   
2  1998     20258    5701355.0                   1   
3  1999     21630    6094817.0                   1   
4  2000     24520    7166551.0                   1   
5  2005     33261    9590228.0                   1   
6  1979      7191    1944814.0                   1   
7  1996     18071    5091901.0                   1   
8  2002     25920    7381552.0                   1   
9  1984      9296    2552604.0                   1   

                                        Longest_Book  
0           Soldadura, Nivel Duo Guía del estudiante  
1                                     مجموعة الفتاوى  
2      Goethes Poetische Werke: Vollständige Ausgabe  
3                     ميخائيل نعيمه المجموعة الكاملة  
4                 Combo - As Crônicas de Gelo e Fogo  
5  幽・遊・白書 完全版 全15巻・全巻セット (幽・遊・白書 完全版 YuYu Hakusho...  
6                     Gordana kraljica Hrvata (1-12)  
7     The Persian Encyclopedia (دايرة المعارف فارسى)  
8  The Works of John Brown of Wamphray (7 Volumes...  
9                             تفسير التحرير والتنوير  

print(yearly_info.tail(10))

     Year Num_Books  Total_Pages Most_Prolific_Month  \
336  1738         3        254.0                   1   
337  1705        10       7538.0                   1   
338  1694         6        571.0                   1   
339  1711        11       4129.0                   1   
340  2021        18       7544.0                   1   
341  1701         2         83.0                   1   
342  1700         4       1202.0                   1   
343  2022         7       1600.0                  12   
344  1679         3        990.0                   1   
345  2023         2        412.0                   5   

                                          Longest_Book  
336  De la conversation: Suivi d’un essai de Jonath...  
337                         روح البيان في تفسير القرآن  
338                                  Cuentos de antaño  
339  Voyages de Monsieur le chevalier Chardin en Pe...  
340  The Navigator's Children (The Last King of Ost...  
341                    Tabiat Işığı ile Hakikati Arama  
342                  Mémoires de M. D'Artagnan, Tome 1  
343                Annabel Horton: Lost Witch of Salem  
344  Strange Stories from a Chinese Studio, Vol. 1 ...  
345                             Short & Happy [or Not]  

Ask ChatGPT or any other LLM chatbot tool to implement this function and compare your work with the one the bot gave you as an answer. Does the chatbot implementation work? Please test it out and verify the correctness of the implementation, explaining the process you followed to prove it.

# Following implementation is done by Chat GPT 4.0:

def books_info(year):
    # filter the dataframe by the given year
    books_in_year = books2[books2['original_publication_date'].dt.year == year]

    # calculate the number of books published that year
    num_books = books_in_year.shape[0]

    # calculate the total number of pages written that year
    total_pages = books_in_year['num_pages'].sum()

    # calculate the most prolific month of that year
    most_prolific_month = books_in_year['original_publication_date'].dt.month.value_counts().idxmax()

    # find the longest book written that year
    longest_book = books_in_year.loc[books_in_year['num_pages'].idxmax()]['title']

    return {
        "Number of books published": num_books,
        "Total number of pages": total_pages,
        "Most prolific month": most_prolific_month,
        "Longest book": longest_book,
    }

print(books_info(2003))

{'Number of books published': 27855, 'Total number of pages': 7902848.0, 'Most prolific month': 1, 'Longest book': 'Soldadura, Nivel Duo Guía del estudiante'}

# Following function is implemented by Bard LLM of Google:

import pandas as pd

def get_book_stats_by_year(books2, year):
  """Get book stats by year.

  Args:
    books2: A pandas DataFrame containing book data.
    year: The year to get book stats for.

  Returns:
    A dictionary containing the following information:
      * The number of books published that year.
      * The total number of pages written that year.
      * The most prolific month of that year.
      * The longest book written that year.
  """

  # Filter the books2 DataFrame to only include books published in the given year.
  books_by_year = books2[books2['original_publication_date'].dt.year == year]

  # Get the number of books published that year.
  num_books_published = len(books_by_year)

  # Get the total number of pages written that year.
  total_pages_written = books_by_year['num_pages'].sum()

  # Get the most prolific month of that year.
  most_prolific_month = books_by_year['original_publication_date'].dt.month.value_counts().nlargest(1).index[0]

  # Get the longest book written that year.
  longest_book = books_by_year[books_by_year['num_pages'] == books_by_year['num_pages'].max()]

  return {
    'num_books_published': num_books_published,
    'total_pages_written': total_pages_written,
    'most_prolific_month': most_prolific_month,
    'longest_book': longest_book
  }

get_book_stats_by_year(books2, 2003)

{'num_books_published': 27855,
 'total_pages_written': 7902848.0,
 'most_prolific_month': 1,
 'longest_book':                                             title  num_pages language  \
 4026121  Soldadura, Nivel Duo Guía del estudiante     9998.0      spa   
 
          average_rating  ratings_count  text_reviews_count author_name  \
 4026121             4.5              2                   0       NCCER   
 
         original_publication_date publication_date  
 4026121                2003-08-08       2012-11-01  }

Analyis and Remarks on the LLM Implementation:

< write an essay here >

RQ 4: Quirks questions about consistency.

You should be sure there are no eponymous (different authors who have precisely the same name) in the author's dataset. Is it true?

eponymous_authors = authors3[authors3.duplicated('name', keep=False)]
if not eponymous_authors.empty:
    print("Eponymous authors found: "+str(eponymous_authors.shape[0]))
    print(eponymous_authors['name'])

Eponymous authors found: 18
8639            Peter  Marshall
14943      Christopher Phillips
19037     William Messner-Loebs
74780           Peter  Marshall
99922             Yordan Yovkov
134763                محمد نجيب
165580      Jackson Butch Guice
171064                محمد نجيب
178267             Q. Hayashida
185467            Dimitar Dimov
193531      Jackson Butch Guice
194321             Q. Hayashida
200003     Christopher Phillips
228145            Yordan Yovkov
270233        James C.L. Carson
311093    William Messner-Loebs
314855            Dimitar Dimov
315853        James C.L. Carson
Name: name, dtype: object

Write a function that, given a list of author_id, outputs a dictionary where each author_id is a key, and the related value is a list with the names of all the books the author has written.

def get_author_books_v0(author_ids):
    author_books = {}
    for author_id in author_ids:
        matching_rows = authors3[authors3['id'] == author_id]
        if not matching_rows.empty:
            author_name = matching_rows.iloc[0]['name']
            # Check if 'author_name' is present in the 'books2' DataFrame
            if 'author_name' in books2.columns:
                books = books2[books2['author_name'] == author_name]['title'].tolist()
                author_books[author_name] = books
            else:
                # Handle the case where 'author_name' column is not found
                author_books[author_name] = ["Author's Books Not Found"]
        else:
            # Handle the case where no matching author is found
            author_books[author_name] = ["Author Not Found"]

    return author_books

What is the longest book title among the books of the top 20 authors regarding their average rating? Is it the longest book title overall?

Top 20 authors by average rating

top_20_authors_v0 = authors3.nlargest(20, 'average_rating')
top_20_author_ids_v0 = top_20_authors_v0['id'].tolist()

Get books of the top 20 authors

top_20_author_books_v0 = get_author_books_v0(top_20_author_ids_v0)

longest_title_v0 = max(max(top_20_author_books_v0.values(), key=len), key=len)

overall_longest_title_v0 = max(books2['title'], key=len)

shortest_title_v0 = min(books2['title'], key=len)

print("Top 20 authors' books:")
for author, books in top_20_author_books_v0.items():
    print(f"{author}: {books}")

Top 20 authors' books:
James T. Holmes: []
Jessie (Pierce) Trebesch: []
Staci Mauney: []
Robert Sidney: ['The Poems of Robert Sidney']
Christine K. Fields: []
Ondeane Lourens: []
Bonnie Kelso: []
Nikos Dimitriou: []
J.M. van Zuiden: []
Archimandrite Gabriel: []
Carlo de Incontrera: []
Lavelle Carlson: []
Tiffany Post: []
Robert     Reed: []
Catherine  Soto: []
Nancy Harding: []
Alex     Johnson: []
Xavier Seoane Rivas: ['A dama da noite']
Fran Moeller Gatins: []
Mark D. Swartz: []

print(f"Longest book title among the top 20 authors: {longest_title_v0}")

Longest book title among the top 20 authors: The Poems of Robert Sidney

if longest_title_v0 == overall_longest_title_v0:
    print("The longest book title among the top 20 authors is the same as the longest book title overall.")
else:
    print("The longest book title among the top 20 authors is not the same as the longest book title overall.")

The longest book title among the top 20 authors is not the same as the longest book title overall.

print(f"Overall Longest book title is: {overall_longest_title_v0}")

Overall Longest book title is: Lecture on Human Happiness: Being the First of a Series of Lectures on That Subject in Which Will Be Comprehended a General Review of the Causes of the Existing Evils of Society [And a Development of Means by Which They May Be Permanently and Effectual...

print(f"Shortest book title overall: {shortest_title_v0}")

Shortest book title overall: Q

I can notice a lot of data of authors who have no books at all, this needs some further cleaning to do a proper analysis. Hence I will clean the authors dataset more according to the presence of author books in books dataset and redo the function implementations and answers to RQ 4.

# Identify author IDs with no books in the books DataFrame
authors_with_books = books2['author_name'].unique()

authors_with_books

array(['J.K. Rowling', 'Douglas Adams', 'Bill Bryson', ..., 'A.C. Spahn',
       'Alexis Koetting', 'Chad A. Clark'], dtype=object)

authors_clean = authors3[authors3['name'].isin(authors_with_books)]

authors_clean.shape[0]

138645

def get_author_books(author_ids):
    author_books = {}
    for author_id in author_ids:
        matching_rows = authors_clean[authors_clean['id'] == author_id]
        if not matching_rows.empty:
            author_name = matching_rows.iloc[0]['name']
            # Check if 'author_id' is present in the 'books2' DataFrame
            if 'author_name' in books2.columns:
                books = books2[books2['author_name'] == author_name]['title'].tolist()
                author_books[author_name] = books
            else:
                # Handle the case where 'author_id' column is not found
                author_books[author_name] = ["Author's Books Not Found"]
        else:
            # Handle the case where no matching author is found
            author_books[author_name] = ["Author Not Found"]

    return author_books

top_20_authors = authors_clean.nlargest(20, 'average_rating')
top_20_author_ids = top_20_authors['id'].tolist()

top_20_author_books = get_author_books(top_20_author_ids)

longest_title = max(max(top_20_author_books.values(), key=len), key=len)

overall_longest_title = max(books2['title'], key=len)

shortest_title = min(books2['title'], key=len)

print("Top 20 authors' books:")
for author, books in top_20_author_books.items():
    print(f"{author}: {books}")

Top 20 authors' books:
Robert Sidney: ['The Poems of Robert Sidney']
Xavier Seoane Rivas: ['A dama da noite']
Lori Walters: ['The Day that Rocked the 4th Dimension']
Sean McSweeney: ['The On-And-On Tin']
Robert Jahn: ['Der salzige Fluss']
E.E.E.: ['A Warm Mirror Neuron On A Memory']
Darryl Scriven: ['The Love Commitment']
Julian Weiss: ['The Mester de Clerecía: Intellectuals and Ideologies in Thirteenth Century Castile', 'Locating the Middle Ages: The Spaces and Places of Medieval Culture']
John F. Wilson: ['Obra Morava en Nicaragua: trasfondo y breve historia']
Becky Long: ['Transition Nutrition: The Easy, Sustainable Way to Change Your Diet AND the Reasons Why You Should Change Now (Volume 1)']
Thaddeus Stevens: ['The Papers Of Thaddeus Stevens Volume 1: January 1814-March 1865']
Donald W. Bartow: ['The Gospel According to Mary, Mother of Jesus']
Peter W. Smorynski: ['A Shadow of Chaos (Universal War: ARM X, #2)']
Rodrigo Duarte Casar: ['Antónimos Anónimos: una Recopilación de Usos Creativos del Lenguaje, Frecuentemente Involuntarios']
Greg Long: ['The New Game Changers: Driving Performance by Focusing on What Matters']
Thaddeus W.H. Leavitt: ['History of Leeds and Grenville, Ontario, from 1749-1879 with Illustrations and Biographical Sketches of Some of its Prominent Men and Pioneers']
George                Smith: ["Smith's Introduction to Industrial Mycology"]
Antonio Rumeu de Armas: ['Alfonso De Ulloa, Introductor de la Cultura Española en Italia', 'En Colom a Barcelona']
Mrs. John King Van Rensselaer: ['Newport, Our Social Capital']
Alan J. Rocke: ['Image and Reality: Kekulé, Kopp, and the Scientific Imagination']

print(f"Longest book title among the top 20 authors: {longest_title}")

Longest book title among the top 20 authors: The Mester de Clerecía: Intellectuals and Ideologies in Thirteenth Century Castile

if longest_title == overall_longest_title:
    print("The longest book title among the top 20 authors is the same as the longest book title overall.")
else:
    print("The longest book title among the top 20 authors is not the same as the longest book title overall.")

The longest book title among the top 20 authors is not the same as the longest book title overall.

print(f"Overall Longest book title is: {overall_longest_title}")

Overall Longest book title is: Lecture on Human Happiness: Being the First of a Series of Lectures on That Subject in Which Will Be Comprehended a General Review of the Causes of the Existing Evils of Society [And a Development of Means by Which They May Be Permanently and Effectual...

print(f"Shortest book title overall: {shortest_title}")

Shortest book title overall: Q

RQ 5: Authors with the most fans to be influential. Let’s have a deeper look.

Plot the top 10 most influential authors regarding their fan count and number of books. Who is the most influential author?

top10fansbasis= authors_clean.nlargest(10,'fans_count')

plt.figure(figsize=(8, 3))
plt.barh(top10fansbasis['name'], top10fansbasis['fans_count'])
plt.xlabel('Number of Fans')
plt.ylabel('Author Name')
plt.title('Top 10 Most Influential Authors on the basis of Fans count')
plt.gca().invert_yaxis()  # Inverting the y-axis to display the most influential at the top
plt.show()

top10worksbasis=authors_clean.nlargest(10,'works_count')

plt.figure(figsize=(8, 3))
plt.barh(top10worksbasis['name'], top10worksbasis['works_count'])
plt.xlabel('Number of Books')
plt.ylabel('Author Name')
plt.title('Top 10 Most Influential Authors on the basis of Number of Books')
plt.gca().invert_yaxis()  # Inverting the y-axis to display the most influential at the top
plt.show()

Now I will combine the two columns to find the overall influence based on the combined metrics.

authors_clean['influence'] = authors_clean['fans_count'] * authors_clean['works_count']

<ipython-input-77-214fb8cd2b99>:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  authors_clean['influence'] = authors_clean['fans_count'] * authors_clean['works_count']

top10authors=authors_clean.nlargest(10,'influence')

plt.figure(figsize=(8, 3))
plt.barh(top10authors['name'], top10authors['influence'])
plt.xlabel('Combined Influence Metric')
plt.ylabel('Author Name')
plt.title('Top 10 Most Influential Authors based on Fans Count and Books Count')
plt.gca().invert_yaxis()  # Inverting the y-axis to display the most influential at the top
plt.show()

Hence, the Most Influential Author is James Patterson.

influential_author_names = top10authors['name'].tolist()

print(influential_author_names)

['James Patterson', 'George R.R. Martin', 'Rick Riordan', 'J.K. Rowling', 'Cassandra Clare', 'Brandon Sanderson', 'Nora Roberts', 'Haruki Murakami', 'Diana Gabaldon', 'Nicholas Sparks']

Have they published any series of books? If any, extract the longest series name among these authors.

I am filtering the dataset only on the basis of the top 10 influential author names:

book_series_data = books2[books2['author_name'].isin(influential_author_names)]

book_series_data.shape[0]

7469

book_series_data.head(3)

	title	num_pages	language	average_rating	ratings_count	text_reviews_count	author_name	original_publication_date	publication_date	format	series_id	series_name	series_position
0	Harry Potter and the Order of the Phoenix (Har...	870.0	eng	4.50	2628006	44716	J.K. Rowling	2003-06-21	2004-09	Paperback	45175	Harry Potter	5
1	Harry Potter and the Sorcerer's Stone (Harry P...	309.0	eng	4.48	7377351	116930	J.K. Rowling	1997-06-26	2003-11-01	Hardcover	45175	Harry Potter	1
2	Harry Potter and the Chamber of Secrets (Harry...	352.0	eng	4.43	2855044	55286	J.K. Rowling	1998-07-02	2003-11-01	Hardcover	45175	Harry Potter	2

series = book_series_data.groupby('author_name')['series_name'].unique()

series

author_name
Brandon Sanderson     [Elantris, Mistborn, Alcatraz Versus The Evil ...
Cassandra Clare       [The Mortal Instruments, The Infernal Devices,...
Diana Gabaldon        [Outlander, The Outlandish Companions, Lord Jo...
George R.R. Martin    [A Song of Ice and Fire, , Wild Cards, The Art...
Haruki Murakami       [海辺のカフカ, , ノルウェイの森, ねじまき鳥クロニクル, The Rat, ねじまき鳥...
J.K. Rowling          [Harry Potter, , Hogwarts Library, Harry Potte...
James Patterson       [, Alex Cross, Women's Murder Club, Maximum Ri...
Nicholas Sparks          [, Jeremy Marsh & Lexie Darnell, The Notebook]
Nora Roberts          [, Gallaghers of Ardmore, Circle Trilogy, The ...
Rick Riordan          [Percy Jackson and the Olympians, Tres Navarre...
Name: series_name, dtype: object

longest_name = series.apply(lambda x: max(x, key=len))

longest_name

author_name
Brandon Sanderson                   Alcatraz Versus The Evil Librarians
Cassandra Clare                   The Mortal Instruments: Graphic Novel
Diana Gabaldon                           Outlander Split-Volume Edition
George R.R. Martin    Game of Thrones / Das Lied von Eis und Feuer (...
Haruki Murakami                                           ねじまき鳥クロニクル #3
J.K. Rowling            Harry Potter Persian/Farsi Split-Volume Edition
James Patterson                       The Best American Mystery Stories
Nicholas Sparks                            Jeremy Marsh & Lexie Darnell
Nora Roberts                           Time and Again: Hornblower-Stone
Rick Riordan          Percy Jackson and the Olympians: The Graphic N...
Name: series_name, dtype: object

longest_series_name = longest_name[longest_name.str.len().idxmax()]

author_with_longest_series=", ".join(book_series_data[book_series_data['series_name']==longest_series_name]['author_name'].unique())

print("Author with the Longest Series Name:", author_with_longest_series)
print("Longest Series Name:", longest_series_name)

Author with the Longest Series Name: George R.R. Martin
Longest Series Name: Game of Thrones / Das Lied von Eis und Feuer (Audible)

How many of these authors have been published in different formats? Provide a meaningful chart on the distribution of the formats and comment on it.

unique_formats = book_series_data.groupby('author_name')['format'].unique()

unique_formats

author_name
Brandon Sanderson     [Mass Market Paperback, Hardcover, ebook, Pape...
Cassandra Clare       [Hardcover, Paperback, Broché, , Mass Market P...
Diana Gabaldon        [Paperback, Mass Market Paperback, Hardcover, ...
George R.R. Martin    [Paperback, Mass Market Paperback, Hardcover, ...
Haruki Murakami       [Paperback, Hardcover, , Taschenbuch, 単行本, Mas...
J.K. Rowling          [Paperback, Hardcover, Mass Market Paperback, ...
James Patterson       [Paperback, Mass Market Paperback, Hardcover, ...
Nicholas Sparks       [Paperback, Hardcover, Mass Market Paperback, ...
Nora Roberts          [Mass Market Paperback, Paperback, , Hardcover...
Rick Riordan          [Hardcover, Paperback, Audio CD, Board Book, ,...
Name: format, dtype: object

formats_count = unique_formats.apply(lambda x: len(x))

formats_count

author_name
Brandon Sanderson     12
Cassandra Clare       12
Diana Gabaldon        11
George R.R. Martin    21
Haruki Murakami       18
J.K. Rowling          15
James Patterson       14
Nicholas Sparks       10
Nora Roberts          27
Rick Riordan          10
Name: format, dtype: int64

import matplotlib.pyplot as plt
plt.figure(figsize=(8, 6))
formats_count.plot(kind='bar')
plt.title('Distribution of Formats for Top 10 Authors')
plt.xlabel('Author Name')
plt.ylabel('Number of Unique Formats')
plt.show()

Provide information about the general response from readers (number of fans, average rating, number of reviews, etc.), divide the authors by gender, and comment about anything eventually related to “structural bias.” You may want to have a look at the following recommended readings: You can even ask ChatGPT or any other LLM chatbot tool: try to formulate a prompt that provides helpful information about it. Put that information in your notebook and provide comments on what you found.

summary_by_gender = top10authors.groupby('gender')[['fans_count', 'average_rating', 'text_reviews_count']].agg(['mean', 'std', 'min', 'max'])

summary_by_gender

	fans_count				average_rating				text_reviews_count
	mean	std	min	max	mean	std	min	max	mean	std	min	max
gender
female	164740.500000	87582.167841	41402	238560	4.265000	0.151987	4.09	4.46	328483.750000	225395.936540	127360	606373
male	201767.333333	107979.658858	86123	339346	4.181667	0.197019	3.96	4.38	249589.833333	78958.792016	167603	354145

Summary:

The table provides insights into the top 10 authors, specifically in terms of 'fans_count,' 'average_rating,' and 'text_reviews_count,' divided by gender (female and male). Here's a summary of the key statistics for each gender:

Female Authors:

The mean 'fans_count' for female authors is approximately 164,740.5, with a standard deviation of 87,582.17. The minimum 'fans_count' is 41,402, and the maximum is 238,560. The mean 'average_rating' for female authors is around 4.265, with a standard deviation of 0.152. The lowest average rating is 4.09, and the highest is 4.46. The mean 'text_reviews_count' for female authors is approximately 328,483.75, with a standard deviation of 225,395.94. The lowest text reviews count is 127,360, and the highest is 606,373.

Male Authors:

The mean 'fans_count' for male authors is about 201,767.33, with a standard deviation of 107,979.66. The minimum 'fans_count' is 86,123, and the maximum is 339,346. The mean 'average_rating' for male authors is approximately 4.182, with a standard deviation of 0.197. The lowest average rating is 3.96, and the highest is 4.38. The mean 'text_reviews_count' for male authors is around 249,589.83, with a standard deviation of 78,958.79. The lowest text reviews count is 167,603, and the highest is 354,145.

I asked ChatGPT to implement a Visualisation for this summary statistics and here it goes:

import seaborn as sns

# Sample data (replace with your actual data)
mean_data = {
    'gender': ['female', 'male'],
    'fans_count_mean': [164740.5, 201767.33],
    'average_rating_mean': [4.265, 4.182],
    'text_reviews_count_mean': [328483.75, 249589.83]
}

# Create a DataFrame from the sample data
mean_df = pd.DataFrame(mean_data)

# Set the style for Seaborn
sns.set(style="whitegrid")

# Create a figure with subplots
fig, axes = plt.subplots(1, 3, figsize=(15, 5))

# Bar chart for mean fans_count
sns.barplot(x="gender", y="fans_count_mean", data=mean_df, ax=axes[0])
axes[0].set(title="Mean Fans Count")

# Bar chart for mean average_rating
sns.barplot(x="gender", y="average_rating_mean", data=mean_df, ax=axes[1])
axes[1].set(title="Mean Average Rating")

# Bar chart for mean text_reviews_count
sns.barplot(x="gender", y="text_reviews_count_mean", data=mean_df, ax=axes[2])
axes[2].set(title="Mean Text Reviews Count")

# Add a common title for the subplots
plt.suptitle("Summary Statistics by Gender")

# Show the plots
plt.show()

# Create box plots to visualize data spread (you can adapt this)
# Example for 'fans_count'
plt.figure(figsize=(8, 3))
sns.boxplot(x='gender', y='fans_count', data=top10authors)
plt.title("Box Plot of Fans Count by Gender")
plt.show()

Conclusions

Fans Count:

Male authors, on average, have a slightly higher number of fans compared to female authors. However, there is significant variability within both groups, as indicated by the standard deviations. The minimum and maximum fans count for both male and female authors is substantial, indicating a wide range of popularity among the top 10 authors.

Average Rating:

Female authors, on average, have a slightly higher average rating compared to male authors. Both groups have relatively high average ratings. The standard deviations for average rating are relatively low, suggesting that most top 10 authors in both groups receive consistently high ratings.

Text Reviews Count:

Female authors have a notably higher mean text reviews count compared to male authors. This indicates that books by female authors in the top 10 receive more text reviews, on average. The standard deviations for text reviews count are high, indicating variability in the number of reviews received by authors in both groups. Overall, it's essential to note that these conclusions are based on the top 10 authors in the dataset and may not be representative of all authors.

Both male and female authors in the top 10 are popular, with a significant number of fans. Female authors, on average, tend to have slightly higher average ratings and receive more text reviews. There is variability in the popularity, average ratings, and reviews count within both groups. However, it's important to consider that these insights are specific to the top 10 authors in the dataset and should not be generalized to all authors. Additional factors, such as the specific books or genres written by these authors, can influence these statistics.

RQ 6: Consider the top 10 authors concerning the number of fans again.

Provide the average time gap between two subsequent publications for a series of books and those not belonging to a series. What do you expect to see, and what is the actual answer to this question?

top10onfansbasis= authors_clean.nlargest(10,'fans_count')

popular_author_names = top10onfansbasis['name'].tolist()

book_data_filtered = books2[books2['author_name'].isin(influential_author_names)]

book_data_filtered.head(2)

	title	num_pages	language	average_rating	ratings_count	text_reviews_count	author_name	original_publication_date	publication_date	format	series_id	series_name	series_position	time_gap
179294	A Song for Lya	208.0	eng	3.94	1787	154	George R.R. Martin	1976-02-01	1976-02-01	Mass Market Paperback				NaT
1183478	Het stervende licht	352.0	nl	3.57	5665	538	George R.R. Martin	1977-01-01	1977-01-01	Paperback				335 days

here the Publication Date column has the value in wrong format, so we correct that area:

book_data_filtered["publication_date"] = pd.to_datetime(book_data_filtered["publication_date"], errors='coerce')
book_data_filtered["publication_date"] = pd.to_datetime(book_data_filtered["publication_date"])
present_date = datetime.now()
book_data_filtered = book_data_filtered[book_data_filtered['publication_date'] <= present_date]
book_data_filtered["publication_date"].max()

<ipython-input-153-bc5a032a9d9f>:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  book_data_filtered["publication_date"] = pd.to_datetime(book_data_filtered["publication_date"], errors='coerce')
<ipython-input-153-bc5a032a9d9f>:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  book_data_filtered["publication_date"] = pd.to_datetime(book_data_filtered["publication_date"])

Timestamp('2021-03-02 00:00:00')

# we are sorting the DataFrame by 'publication_date' within each series
book_data_filtered = book_data_filtered.sort_values(by=['series_name', 'publication_date'])

# and then calculating time gap between subsequent publications
book_data_filtered['time_gap'] = book_data_filtered.groupby('series_name')['publication_date'].diff()

# the average time gap for books belonging to a series
avg_time_gap_within_series = book_data_filtered[book_data_filtered['series_name']!='']['time_gap'].mean()

# Calculate the average time gap for books not belonging to a series
avg_time_gap_not_in_series = book_data_filtered[book_data_filtered['series_name']=='']['time_gap'].mean()

print(f'Average time gap between two subsequent publications for a series of books is {avg_time_gap_within_series.days} days')
print(f'\nAverage time gap between two subsequent publications for books not belonging to a series is {avg_time_gap_not_in_series.days} days')

Average time gap between two subsequent publications for a series of books is 89 days

Average time gap between two subsequent publications for books not belonging to a series is 8 days

For each of the authors, give a convenient plot showing how many books has the given author published UP TO a given year. Are these authors contemporary with each other? Can you notice a range of years where their production rate was higher?

# we get the publication year
book_data_filtered['publication_year'] = book_data_filtered['publication_date'].dt.year

# to count the cumulative number of books published after group by author and year
book_data_filtered['cumulative_books'] = book_data_filtered.groupby(['author_name', 'publication_year']).cumcount() + 1

book_data_filtered[['author_name','publication_year','cumulative_books']]

	author_name	publication_year	cumulative_books
179294	George R.R. Martin	1976	1
1183478	George R.R. Martin	1977	1
3942614	George R.R. Martin	1978	1
781039	George R.R. Martin	1978	2
486916	George R.R. Martin	1979	1
...	...	...	...
3422117	Haruki Murakami	2012	85
4710419	Haruki Murakami	2013	77
5498749	Haruki Murakami	2013	78
6101280	Haruki Murakami	2014	57
6447392	Haruki Murakami	2014	58

7156 rows × 3 columns

# Extract the year from the 'publication_date' and create a new column 'publication_year'
book_data_filtered['publication_year'] = book_data_filtered['publication_date'].dt.year

book_counts = book_data_filtered.groupby(['author_name', 'publication_year']).size().unstack(level=0, fill_value=0)
#the above line of code groups the data by author_name and publication_year unique combinations and then unstacks the resultant
# into separate columns of author_names and rows of publication_year. The author who has a book published in a given year will have a cell value 1, 2, 3...etc
# based on the number of books published by that author in that given year. I am using this unstack function of the pandas dataframe to store a df into
# the book_counts.

book_counts.head(5)

author_name	Brandon Sanderson	Cassandra Clare	Diana Gabaldon	George R.R. Martin	Haruki Murakami	J.K. Rowling	James Patterson	Nicholas Sparks	Nora Roberts	Rick Riordan
publication_year
1976	0	0	0	2	0	0	0	0	0	0
1977	0	0	0	1	0	0	0	0	0	0
1978	0	0	0	2	0	0	0	0	0	0
1979	0	0	0	4	2	0	0	0	0	0
1980	0	0	0	2	1	0	1	0	0	0

cumulative_counts = book_counts.cumsum()

cumulative_counts.head(5)

author_name	Brandon Sanderson	Cassandra Clare	Diana Gabaldon	George R.R. Martin	Haruki Murakami	J.K. Rowling	James Patterson	Nicholas Sparks	Nora Roberts	Rick Riordan
publication_year
1976	0	0	0	2	0	0	0	0	0	0
1977	0	0	0	3	0	0	0	0	0	0
1978	0	0	0	5	0	0	0	0	0	0
1979	0	0	0	9	2	0	0	0	0	0
1980	0	0	0	11	3	0	1	0	0	0

The cumsum() function helped in calculating the cumulative number of books published by the author upto a certain year. For example, George RR Martin has 2 books published till 1976, 2+1 till 1977, 2+1+2=5 till 1978 and so on...

# then we plot the cumulative counts for each author
cumulative_counts.plot(figsize=(10,5))
plt.title('Cumulative Number of Books Published by Author per Year')
plt.xlabel('Year')
plt.ylabel('Cumulative Number of Books')
plt.legend(title='Author')
plt.grid()
years = cumulative_counts.index
year_step = 3
years_to_display = years[::year_step]
plt.xticks(years_to_display)
plt.show()

Looking at the graph, we can infer that, these top 10 popular authors are contemporary to each other. Their production curve has a sharp rise somewhere between 2009 and 2015 and after 2015, the production rate curve flattens. We can say, between approximately 2009 and 2015, their production rate was higher.

[RQ7] Estimating probabilities is a core skill for a data scientist: show us your best!

Question 1

import json
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)

booko= pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", nrows=10, lines= True)
booko

	id	title	authors	author_name	author_id	work_id	isbn	isbn13	asin	language	average_rating	rating_dist	ratings_count	text_reviews_count	publication_date	original_publication_date	format	edition_information	image_url	publisher	num_pages	series_id	series_name	series_position	shelves	description
0	2	Harry Potter and the Order of the Phoenix (Har...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	2809203	0439358078	9780439358071		eng	4.50	5:1674064|4:664833|3:231195|2:41699|1:16215|to...	2628006	44716	2004-09	2003-06-21	Paperback	US Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc.	870	45175	Harry Potter	5	[{'name': 'to-read', 'count': 324191}, {'name'...	There is a door at the end of a silent corrido...
1	3	Harry Potter and the Sorcerer's Stone (Harry P...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	4640799				eng	4.48	5:4801606|4:1681521|3:623286|2:145898|1:125040...	7377351	116930	2003-11-01	1997-06-26	Hardcover	Library Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc	309	45175	Harry Potter	1	[{'name': 'fantasy', 'count': 63540}, {'name':...	Harry Potter's life is miserable. His parents ...
2	4	Harry Potter and the Chamber of Secrets (Harry...	None	J.K. Rowling	1077326	6231171	0439554896	9780439554893		eng	4.43	5:1690166|4:781011|3:313727|2:54687|1:15453|to...	2855044	55286	2003-11-01	1998-07-02	Hardcover		https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	352	45175	Harry Potter	2	[{'name': 'to-read', 'count': 282341}, {'name'...	The Dursleys were so mean and hideous that sum...
3	5	Harry Potter and the Prisoner of Azkaban (Harr...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	2402163	043965548X	9780439655484		eng	4.57	5:1994597|4:696545|3:212678|2:28915|1:13959|to...	2946694	58023	2004-05-01	1999-07-08	Mass Market Paperback		https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc.	435	45175	Harry Potter	3	[{'name': 'to-read', 'count': 292815}, {'name'...	For twelve long years, the dread fortress of A...
4	6	Harry Potter and the Goblet of Fire (Harry Pot...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	3046572				eng	4.56	5:1808039|4:663849|3:193604|2:27759|1:12425|to...	2705676	48637	2002-09-28	2000-07-08	Paperback	First Scholastic Trade Paperback Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	734	45175	Harry Potter	4	[{'name': 'to-read', 'count': 287086}, {'name'...	Harry Potter is midway through his training as...
5	7	The Harry Potter Collection (Harry Potter, #1-6)	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	21457570	0439887453	9780439887458		eng	4.73	5:25063|4:4467|3:1103|2:227|1:282|total:31142	31142	975	2006-09-01	2005-01-01	Paperback	Box Set	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic		45175	Harry Potter	1-6	[{'name': 'to-read', 'count': 5809}, {'name': ...	<div>Six years of magic, adventure, and myster...
6	8	Harry Potter Boxed Set, Books 1-5 (Harry Potte...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	21457576	0439682584	9780439682589		eng	4.79	5:49438|4:6112|3:1525|2:354|1:534|total:57963	57963	183	2004-09-13	2003-10-01	Paperback		https://s.gr-assets.com/assets/nophoto/book/11...	Scholastic	2690				[{'name': 'to-read', 'count': 7030}, {'name': ...	Box Set containing Harry Potter and the Sorcer...
7	10	Harry Potter Collection (Harry Potter, #1-6)	None	J.K. Rowling	1077326	21457570	0439827604	9780439827607		eng	4.73	5:25063|4:4467|3:1103|2:227|1:282|total:31142	31142	975	2005-09-12	2005-01-01	Hardcover	Box Set	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	3342	45175	Harry Potter	1-6	[{'name': 'to-read', 'count': 5809}, {'name': ...	Six years of magic, adventure, and mystery mak...
8	11	The Hitchhiker's Guide to the Galaxy (Hitchhik...	None	Douglas Adams	4	3078186				eng	4.22	5:753962|4:436665|3:206876|2:60681|1:32955|tot...	1491139	31417	2005	1979-10-12	Mass Market Paperback	Movie Tie-In Edition	https://i.gr-assets.com/images/S/compressed.ph...	Del Rey Books	216	40957	The Hitchhiker's Guide to the Galaxy	1	[{'name': 'to-read', 'count': 716080}, {'name'...	Seconds before the Earth is demolished to make...
9	12	The Ultimate Hitchhiker's Guide: Five Complete...	None	Douglas Adams	4	135328	0517226952	9780517226957		eng	4.36	5:167705|4:81013|3:32283|2:8665|1:4360|total:2...	294026	5429	2005-11-01	1996-01-17	Leather Bound		https://i.gr-assets.com/images/S/compressed.ph...	Gramercy Books	815	40957	The Hitchhiker's Guide to the Galaxy	0.5-5	[{'name': 'to-read', 'count': 128191}, {'name'...	At last in paperback in one complete volume, h...

booko['rating_dist']

0    5:1674064|4:664833|3:231195|2:41699|1:16215|to...
1    5:4801606|4:1681521|3:623286|2:145898|1:125040...
2    5:1690166|4:781011|3:313727|2:54687|1:15453|to...
3    5:1994597|4:696545|3:212678|2:28915|1:13959|to...
4    5:1808039|4:663849|3:193604|2:27759|1:12425|to...
5        5:25063|4:4467|3:1103|2:227|1:282|total:31142
6        5:49438|4:6112|3:1525|2:354|1:534|total:57963
7        5:25063|4:4467|3:1103|2:227|1:282|total:31142
8    5:753962|4:436665|3:206876|2:60681|1:32955|tot...
9    5:167705|4:81013|3:32283|2:8665|1:4360|total:2...
Name: rating_dist, dtype: object

def createcounter(x):
    listo= x.split("|") # make a list of the individual ratings
    my_dict= {}
    for s in listo:
        key, value = s.split(':') #split each rating into key and value(was string before)
        my_dict[key] = int(value)# make a dictionnary out of it
    countocount= 0
    if my_dict['5']/ my_dict['total']> 0.3:
        countocount+=1 #The books that have achieved more than 30% ratings above 4 will get marked with a 1, the others with a 0
    return countocount

chunksize = 10**5
sicount=0  #Variable to count the number of books with more than 30% ratings above 4
universe = 0 #Variable to count the number of rated books in total
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize,lines=True ):
    chunk = chunk[chunk["ratings_count"] > 0 ]#Includes only the rows in chunk, that have ratings
    universe += len(chunk) #number of rows that the chunk contains
    chunk["siono"] = chunk.apply(lambda row: createcounter(row["rating_dist"]), axis=1) #Calls the function createcounter for every single row in the chunk and stores the value 1 or in a new column 'siono'
    sicount += len(chunk[chunk["siono"] == 1 ]) # number of rows in the chunk, with more than 30% ratings above 4

print(sicount/universe) #probability that a book has over 30% of the ratings above 4

0.5221711201578421

Question 2

# Estimate the probability that an author publishes a new book within two years from its last work.
# Assumptions:
#-If a book is published in a new format it is considered as new publication
#-Also a series of books is considered as new publication

import json
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
from collections import defaultdict
from datetime import datetime
from statistics import mean

booko2= pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", nrows=10, lines= True)
booko2

	id	title	authors	author_name	author_id	work_id	isbn	isbn13	asin	language	average_rating	rating_dist	ratings_count	text_reviews_count	publication_date	original_publication_date	format	edition_information	image_url	publisher	num_pages	series_id	series_name	series_position	shelves	description
0	2	Harry Potter and the Order of the Phoenix (Har...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	2809203	0439358078	9780439358071		eng	4.50	5:1674064|4:664833|3:231195|2:41699|1:16215|to...	2628006	44716	2004-09	2003-06-21	Paperback	US Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc.	870	45175	Harry Potter	5	[{'name': 'to-read', 'count': 324191}, {'name'...	There is a door at the end of a silent corrido...
1	3	Harry Potter and the Sorcerer's Stone (Harry P...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	4640799				eng	4.48	5:4801606|4:1681521|3:623286|2:145898|1:125040...	7377351	116930	2003-11-01	1997-06-26	Hardcover	Library Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc	309	45175	Harry Potter	1	[{'name': 'fantasy', 'count': 63540}, {'name':...	Harry Potter's life is miserable. His parents ...
2	4	Harry Potter and the Chamber of Secrets (Harry...	None	J.K. Rowling	1077326	6231171	0439554896	9780439554893		eng	4.43	5:1690166|4:781011|3:313727|2:54687|1:15453|to...	2855044	55286	2003-11-01	1998-07-02	Hardcover		https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	352	45175	Harry Potter	2	[{'name': 'to-read', 'count': 282341}, {'name'...	The Dursleys were so mean and hideous that sum...
3	5	Harry Potter and the Prisoner of Azkaban (Harr...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	2402163	043965548X	9780439655484		eng	4.57	5:1994597|4:696545|3:212678|2:28915|1:13959|to...	2946694	58023	2004-05-01	1999-07-08	Mass Market Paperback		https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc.	435	45175	Harry Potter	3	[{'name': 'to-read', 'count': 292815}, {'name'...	For twelve long years, the dread fortress of A...
4	6	Harry Potter and the Goblet of Fire (Harry Pot...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	3046572				eng	4.56	5:1808039|4:663849|3:193604|2:27759|1:12425|to...	2705676	48637	2002-09-28	2000-07-08	Paperback	First Scholastic Trade Paperback Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	734	45175	Harry Potter	4	[{'name': 'to-read', 'count': 287086}, {'name'...	Harry Potter is midway through his training as...
5	7	The Harry Potter Collection (Harry Potter, #1-6)	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	21457570	0439887453	9780439887458		eng	4.73	5:25063|4:4467|3:1103|2:227|1:282|total:31142	31142	975	2006-09-01	2005-01-01	Paperback	Box Set	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic		45175	Harry Potter	1-6	[{'name': 'to-read', 'count': 5809}, {'name': ...	<div>Six years of magic, adventure, and myster...
6	8	Harry Potter Boxed Set, Books 1-5 (Harry Potte...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	21457576	0439682584	9780439682589		eng	4.79	5:49438|4:6112|3:1525|2:354|1:534|total:57963	57963	183	2004-09-13	2003-10-01	Paperback		https://s.gr-assets.com/assets/nophoto/book/11...	Scholastic	2690				[{'name': 'to-read', 'count': 7030}, {'name': ...	Box Set containing Harry Potter and the Sorcer...
7	10	Harry Potter Collection (Harry Potter, #1-6)	None	J.K. Rowling	1077326	21457570	0439827604	9780439827607		eng	4.73	5:25063|4:4467|3:1103|2:227|1:282|total:31142	31142	975	2005-09-12	2005-01-01	Hardcover	Box Set	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	3342	45175	Harry Potter	1-6	[{'name': 'to-read', 'count': 5809}, {'name': ...	Six years of magic, adventure, and mystery mak...
8	11	The Hitchhiker's Guide to the Galaxy (Hitchhik...	None	Douglas Adams	4	3078186				eng	4.22	5:753962|4:436665|3:206876|2:60681|1:32955|tot...	1491139	31417	2005	1979-10-12	Mass Market Paperback	Movie Tie-In Edition	https://i.gr-assets.com/images/S/compressed.ph...	Del Rey Books	216	40957	The Hitchhiker's Guide to the Galaxy	1	[{'name': 'to-read', 'count': 716080}, {'name'...	Seconds before the Earth is demolished to make...
9	12	The Ultimate Hitchhiker's Guide: Five Complete...	None	Douglas Adams	4	135328	0517226952	9780517226957		eng	4.36	5:167705|4:81013|3:32283|2:8665|1:4360|total:2...	294026	5429	2005-11-01	1996-01-17	Leather Bound		https://i.gr-assets.com/images/S/compressed.ph...	Gramercy Books	815	40957	The Hitchhiker's Guide to the Galaxy	0.5-5	[{'name': 'to-read', 'count': 128191}, {'name'...	At last in paperback in one complete volume, h...

grouped = booko2.groupby('author_id')['original_publication_date']
grouped
author_dict = grouped.apply(list).to_dict()
author_dict

{4: ['1979-10-12', '1996-01-17'],
 1077326: ['2003-06-21',
  '1997-06-26',
  '1998-07-02',
  '1999-07-08',
  '2000-07-08',
  '2005-01-01',
  '2003-10-01',
  '2005-01-01']}

chunksize= 10**4
chunks=[]
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
    chunks.append(chunk[['author_id', 'original_publication_date']])
df = pd.concat(chunks, axis=0)
grouped = df.groupby('author_id')['original_publication_date'] #selects all the books with the same author and stores the original publication dates in a list 
author_dict = grouped.apply(list).to_dict() # make a dictionnary out of it
authorslonger2= 0 #Count for authors that had longer than 2 years on average to publish a new book
authorsfaster2=0 ##Count for authors that were faster than 2 years on average to publish a new book
for author_id, original_publication_date in author_dict.items():
    try:
        original_publication_date = sorted([datetime.strptime(date, '%Y-%m-%d') for date in original_publication_date if date is not None]) #convert them to datetime objects
    except ValueError:
        continue # If the convertion can't be done the author is skipped
    differences = [] #  Variable to calculate the difference between the the publications of an author 
    differences_auth=[] # Variable to calculate the average calculation time of the authors
    for i in range(len(original_publication_date)-1):
        try:
            difference = original_publication_date[i+1] - original_publication_date[i]
            differences.append(difference.total_seconds()/(3600*24*360))
        except TypeError: # If the calculation can't be done the author is skipped
            continue
    if differences: # Handling the exception of an empty list
        average_difference = mean(differences)       
        if average_difference >= 2:
            authorslonger2 += 1
        if average_difference <= 2:
            authorsfaster2 += 1
    else:
        continue
prob_faster2= authorsfaster2/(authorslonger2+authorsfaster2)
print(prob_faster2)

0.8973156401944895

Question 3

import json
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)

booko2= pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", nrows=10, lines= True)
booko2

	id	title	authors	author_name	author_id	work_id	isbn	isbn13	asin	language	average_rating	rating_dist	ratings_count	text_reviews_count	publication_date	original_publication_date	format	edition_information	image_url	publisher	num_pages	series_id	series_name	series_position	shelves	description
0	2	Harry Potter and the Order of the Phoenix (Har...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	2809203	0439358078	9780439358071		eng	4.50	5:1674064|4:664833|3:231195|2:41699|1:16215|to...	2628006	44716	2004-09	2003-06-21	Paperback	US Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc.	870	45175	Harry Potter	5	[{'name': 'to-read', 'count': 324191}, {'name'...	There is a door at the end of a silent corrido...
1	3	Harry Potter and the Sorcerer's Stone (Harry P...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	4640799				eng	4.48	5:4801606|4:1681521|3:623286|2:145898|1:125040...	7377351	116930	2003-11-01	1997-06-26	Hardcover	Library Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc	309	45175	Harry Potter	1	[{'name': 'fantasy', 'count': 63540}, {'name':...	Harry Potter's life is miserable. His parents ...
2	4	Harry Potter and the Chamber of Secrets (Harry...	None	J.K. Rowling	1077326	6231171	0439554896	9780439554893		eng	4.43	5:1690166|4:781011|3:313727|2:54687|1:15453|to...	2855044	55286	2003-11-01	1998-07-02	Hardcover		https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	352	45175	Harry Potter	2	[{'name': 'to-read', 'count': 282341}, {'name'...	The Dursleys were so mean and hideous that sum...
3	5	Harry Potter and the Prisoner of Azkaban (Harr...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	2402163	043965548X	9780439655484		eng	4.57	5:1994597|4:696545|3:212678|2:28915|1:13959|to...	2946694	58023	2004-05-01	1999-07-08	Mass Market Paperback		https://i.gr-assets.com/images/S/compressed.ph...	Scholastic Inc.	435	45175	Harry Potter	3	[{'name': 'to-read', 'count': 292815}, {'name'...	For twelve long years, the dread fortress of A...
4	6	Harry Potter and the Goblet of Fire (Harry Pot...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	3046572				eng	4.56	5:1808039|4:663849|3:193604|2:27759|1:12425|to...	2705676	48637	2002-09-28	2000-07-08	Paperback	First Scholastic Trade Paperback Edition	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	734	45175	Harry Potter	4	[{'name': 'to-read', 'count': 287086}, {'name'...	Harry Potter is midway through his training as...
5	7	The Harry Potter Collection (Harry Potter, #1-6)	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	21457570	0439887453	9780439887458		eng	4.73	5:25063|4:4467|3:1103|2:227|1:282|total:31142	31142	975	2006-09-01	2005-01-01	Paperback	Box Set	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic		45175	Harry Potter	1-6	[{'name': 'to-read', 'count': 5809}, {'name': ...	<div>Six years of magic, adventure, and myster...
6	8	Harry Potter Boxed Set, Books 1-5 (Harry Potte...	[{'id': '1077326', 'name': 'J.K. Rowling', 'ro...	J.K. Rowling	1077326	21457576	0439682584	9780439682589		eng	4.79	5:49438|4:6112|3:1525|2:354|1:534|total:57963	57963	183	2004-09-13	2003-10-01	Paperback		https://s.gr-assets.com/assets/nophoto/book/11...	Scholastic	2690				[{'name': 'to-read', 'count': 7030}, {'name': ...	Box Set containing Harry Potter and the Sorcer...
7	10	Harry Potter Collection (Harry Potter, #1-6)	None	J.K. Rowling	1077326	21457570	0439827604	9780439827607		eng	4.73	5:25063|4:4467|3:1103|2:227|1:282|total:31142	31142	975	2005-09-12	2005-01-01	Hardcover	Box Set	https://i.gr-assets.com/images/S/compressed.ph...	Scholastic	3342	45175	Harry Potter	1-6	[{'name': 'to-read', 'count': 5809}, {'name': ...	Six years of magic, adventure, and mystery mak...
8	11	The Hitchhiker's Guide to the Galaxy (Hitchhik...	None	Douglas Adams	4	3078186				eng	4.22	5:753962|4:436665|3:206876|2:60681|1:32955|tot...	1491139	31417	2005	1979-10-12	Mass Market Paperback	Movie Tie-In Edition	https://i.gr-assets.com/images/S/compressed.ph...	Del Rey Books	216	40957	The Hitchhiker's Guide to the Galaxy	1	[{'name': 'to-read', 'count': 716080}, {'name'...	Seconds before the Earth is demolished to make...
9	12	The Ultimate Hitchhiker's Guide: Five Complete...	None	Douglas Adams	4	135328	0517226952	9780517226957		eng	4.36	5:167705|4:81013|3:32283|2:8665|1:4360|total:2...	294026	5429	2005-11-01	1996-01-17	Leather Bound		https://i.gr-assets.com/images/S/compressed.ph...	Gramercy Books	815	40957	The Hitchhiker's Guide to the Galaxy	0.5-5	[{'name': 'to-read', 'count': 128191}, {'name'...	At last in paperback in one complete volume, h...

booko3=pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/archive/list.json/list.json", nrows=10, lines=True)
booko3

	id	title	description	description_html	num_pages	num_books	num_voters	created_date	tags	num_likes	created_by	num_comments	books
0	2	The Worst Books of All Time	What do you think are the worst books ever wri...	\n What do you think are the worst books ...	74	7395	18260	May 20th, 2008	[abominable, abomination, awful, bad, disgusti...	175	{'name': 'Michael Economy', 'id': '73'}	2570	[{'book_id': '41865', 'title': 'Twilight', 'au...
1	3	Best Science Fiction & Fantasy Books	Anything in the science fiction or fantasy gen...	\n Anything in the science fiction or fan...	71	7023	21747	May 29th, 2008	[best-fantasy, best-science-fiction, earliest-...	2989	{'name': 'deleted user', 'id': ''}	307	[{'book_id': '375802', 'title': 'Ender's Game'...
2	4	Best Books of 2008	The best books first published during 2008.See...	\n The best books first published during ...	17	1678	6939	May 29th, 2008	[2008, best, by-year, earliest-list, fiction, ...	59	{'name': 'deleted user', 'id': ''}	181	[{'book_id': '2767052', 'title': 'The Hunger G...
3	5	Best Books of the Decade: 2000s	The best books published during the 2000s deca...	\n The best books published during the 20...	70	6919	28249	May 29th, 2008	[2000, 2001, 2002, 2003, 2004, 2005, 2006, 200...	1192	{'name': 'deleted user', 'id': ''}	163	[{'book_id': '136251', 'title': 'Harry Potter ...
4	6	Best Books of the 20th Century	The best books published during the 20th centu...	\n The best books published during the 20...	76	7600	49437	May 29th, 2008	[20th, 20th-century, best, by-century, by-year...	6083	{'name': 'deleted user', 'id': ''}	510	[{'book_id': '2657', 'title': 'To Kill a Mocki...
5	7	Best Books of the 21st Century	The best books published during the 21st centu...	\n The best books published during the 21...	91	9032	21393	May 29th, 2008	[2001, 2002, 2003, 2004, 2005, 2006, 2007, 200...	2024	{'name': 'deleted user', 'id': ''}	280	[{'book_id': '136251', 'title': 'Harry Potter ...
6	8	Thickest Books Ever	Original novel, not omnibus editions.500 pages...	\n Original novel, not omnibus editions.<...	9	862	2602	June 4th, 2008	[500-pages, 500-pages-plus, big-books, earlies...	118	{'name': 'Michael Economy', 'id': '73'}	104	[{'book_id': '6', 'title': 'Harry Potter and t...
7	9	Best Books of the Decade: 1980s	The best books published during the 1980s deca...	\n The best books published during the 19...	21	2059	2323	June 6th, 2008	[1980, 1980s, 1981, 1982, 1983, 1984, 1985, 19...	240	{'name': 'deleted user', 'id': ''}	41	[{'book_id': '38447', 'title': 'The Handmaid's...
8	10	Best books for an African Safari	Best books to read on an African Safari. Books...	\n Best books to read on an African Safar...	5	445	705	June 9th, 2008	[africa, african, earliest-list, location, saf...	103	{'name': 'deleted user', 'id': ''}	9	[{'book_id': '7244', 'title': 'The Poisonwood ...
9	11	Best Crime & Mystery Books	The best of crime and mystery books.If the boo...	\n The best of crime and mystery books.<b...	62	6112	14241	June 10th, 2008	[best, crime, crime-mystery, mystery]	1827	{'name': 'deleted user', 'id': ''}	138	[{'book_id': '2429135', 'title': 'The Girl wit...

value2 = booko3.loc[0, 'books']
value2

[{'book_id': '41865',
  'title': 'Twilight',
  'author_id': '941441',
  'author': 'Stephenie Meyer',
  'position': {'ranking': 1, 'score': 527144, 'votes': 5303}},
 {'book_id': '1162543',
  'title': 'Breaking Dawn',
  'author_id': '941441',
  'author': 'Stephenie Meyer',
  'position': {'ranking': 2, 'score': 400813, 'votes': 4061}},
 {'book_id': '49041',
  'title': 'New Moon',
  'author_id': '941441',
  'author': 'Stephenie Meyer',
  'position': {'ranking': 3, 'score': 356742, 'votes': 3648}},
 {'book_id': '428263',
  'title': 'Eclipse',
  'author_id': '941441',
  'author': 'Stephenie Meyer',
  'position': {'ranking': 4, 'score': 323657, 'votes': 3338}},
 {'book_id': '10818853',
  'title': 'Fifty Shades of Grey',
  'author_id': '4725841',
  'author': 'E.L. James',
  'position': {'ranking': 5, 'score': 231106, 'votes': 2356}},
 {'book_id': '6263078',
  'title': 'Miles to Go',
  'author_id': '990148',
  'author': 'Miley Cyrus',
  'position': {'ranking': 6, 'score': 175882, 'votes': 1799}},
 {'book_id': '6076107',
  'title': 'Guilty: Liberal "Victims" and Their Assault on America',
  'author_id': '2761',
  'author': 'Ann Coulter',
  'position': {'ranking': 7, 'score': 110457, 'votes': 1145}},
 {'book_id': '3090465',
  'title': 'The Twilight Saga',
  'author_id': '941441',
  'author': 'Stephenie Meyer',
  'position': {'ranking': 8, 'score': 92499, 'votes': 973}},
 {'book_id': '564449',
  'title': 'Scientology: The Fundamentals of Thought',
  'author_id': '33503',
  'author': 'L. Ron Hubbard',
  'position': {'ranking': 9, 'score': 90584, 'votes': 947}},
 {'book_id': '968',
  'title': 'The Da Vinci Code',
  'author_id': '630',
  'author': 'Dan Brown',
  'position': {'ranking': 10, 'score': 85252, 'votes': 875}},
 {'book_id': '4013201',
  'title': 'Hannah Montana and Miley Cyrus: Best of Both Worlds Concert',
  'author_id': '990148',
  'author': 'Miley Cyrus',
  'position': {'ranking': 11, 'score': 77032, 'votes': 809}},
 {'book_id': '1812457',
  'title': 'The Shack',
  'author_id': '15481463',
  'author': 'William Paul Young',
  'position': {'ranking': 12, 'score': 75936, 'votes': 774}},
 {'book_id': '747061',
  'title': 'Book of Mormon, Doctrine and Covenants, Pearl of Great Price',
  'author_id': '1367163',
  'author': 'The Church of Jesus Christ of Latter-day Saints',
  'position': {'ranking': 13, 'score': 66279, 'votes': 698}},
 {'book_id': '2183067',
  'title': 'Hannah Montana 2/Meet Miley Cyrus',
  'author_id': '990148',
  'author': 'Miley Cyrus',
  'position': {'ranking': 14, 'score': 60722, 'votes': 651}},
 {'book_id': '48625',
  'title': 'The No Spin Zone: Confrontations with the Powerful and Famous in America',
  'author_id': '27281',
  'author': "Bill O'Reilly",
  'position': {'ranking': 15, 'score': 57981, 'votes': 615}},
 {'book_id': '993455',
  'title': "An Inconvenient Book: Real Solutions to the World's Biggest Problems",
  'author_id': '188932',
  'author': 'Glenn Beck',
  'position': {'ranking': 16, 'score': 57043, 'votes': 610}},
 {'book_id': '569357',
  'title': 'Let Freedom Ring: Winning the War of Liberty over Liberalism',
  'author_id': '140720',
  'author': 'Sean Hannity',
  'position': {'ranking': 17, 'score': 53321, 'votes': 575}},
 {'book_id': '3975774',
  'title': 'Evermore',
  'author_id': '200317',
  'author': 'Alyson Noel',
  'position': {'ranking': 18, 'score': 53284, 'votes': 554}},
 {'book_id': '19501',
  'title': 'Eat, Pray, Love',
  'author_id': '11679',
  'author': 'Elizabeth Gilbert',
  'position': {'ranking': 19, 'score': 52598, 'votes': 549}},
 {'book_id': '7937462',
  'title': 'The Short Second Life of Bree Tanner',
  'author_id': '941441',
  'author': 'Stephenie Meyer',
  'position': {'ranking': 20, 'score': 51003, 'votes': 550}},
 {'book_id': '9742',
  'title': 'The Audacity of Hope: Thoughts on Reclaiming the American Dream',
  'author_id': '6356',
  'author': 'Barack Obama',
  'position': {'ranking': 21, 'score': 50947, 'votes': 530}},
 {'book_id': '7455',
  'title': 'Sex and the City',
  'author_id': '4415',
  'author': 'Candace Bushnell',
  'position': {'ranking': 22, 'score': 48558, 'votes': 516}},
 {'book_id': '5107',
  'title': 'The Catcher in the Rye',
  'author_id': '819789',
  'author': 'J.D. Salinger',
  'position': {'ranking': 23, 'score': 48407, 'votes': 501}},
 {'book_id': '240469',
  'title': 'Deliver Us from Evil: Defeating Terrorism, Despotism, and Liberalism',
  'author_id': '140720',
  'author': 'Sean Hannity',
  'position': {'ranking': 24, 'score': 47115, 'votes': 515}},
 {'book_id': '119322',
  'title': 'The Golden Compass',
  'author_id': '3618',
  'author': 'Philip Pullman',
  'position': {'ranking': 25, 'score': 46347, 'votes': 481}},
 {'book_id': '8714',
  'title': 'An Inconvenient Truth: The Planetary Emergency of Global Warming and What We Can Do About It',
  'author_id': '5658',
  'author': 'Al Gore',
  'position': {'ranking': 26, 'score': 40940, 'votes': 426}},
 {'book_id': '8752457',
  'title': 'First Step 2 Forever',
  'author_id': '4019884',
  'author': 'Justin Bieber',
  'position': {'ranking': 27, 'score': 40534, 'votes': 432}},
 {'book_id': '11857408',
  'title': 'Fifty Shades Darker',
  'author_id': '4725841',
  'author': 'E.L. James',
  'position': {'ranking': 28, 'score': 40421, 'votes': 431}},
 {'book_id': '675626',
  'title': 'Scientology 8-8008: How to Increase Your Spirituality Ability from Zero to Infinity',
  'author_id': '33503',
  'author': 'L. Ron Hubbard',
  'position': {'ranking': 29, 'score': 36435, 'votes': 403}},
 {'book_id': '6411961',
  'title': 'The Lost Symbol',
  'author_id': '630',
  'author': 'Dan Brown',
  'position': {'ranking': 30, 'score': 35350, 'votes': 369}},
 {'book_id': '7613',
  'title': 'Animal Farm',
  'author_id': '3706',
  'author': 'George Orwell',
  'position': {'ranking': 31, 'score': 33440, 'votes': 347}},
 {'book_id': '8135213',
  'title': 'Justin Bieber: His World',
  'author_id': '2992196',
  'author': 'Riley Brooks',
  'position': {'ranking': 32, 'score': 32972, 'votes': 358}},
 {'book_id': '9416',
  'title': 'Confessions of a Shopaholic',
  'author_id': '6160',
  'author': 'Sophie Kinsella',
  'position': {'ranking': 33, 'score': 32962, 'votes': 350}},
 {'book_id': '3268926',
  'title': 'The Christmas Sweater',
  'author_id': '188932',
  'author': 'Glenn Beck',
  'position': {'ranking': 34, 'score': 31261, 'votes': 347}},
 {'book_id': '96833',
  'title': 'I Want to Tell You: My Response to Your Letters, Your Messages, Your Questions',
  'author_id': '1744933',
  'author': 'O.J. Simpson',
  'position': {'ranking': 35, 'score': 31194, 'votes': 344}},
 {'book_id': '252914',
  'title': "The O'Reilly Factor: The Good, the Bad, and the Completely Ridiculous in American Life",
  'author_id': '27281',
  'author': "Bill O'Reilly",
  'position': {'ranking': 36, 'score': 30375, 'votes': 347}},
 {'book_id': '13536860',
  'title': 'Fifty Shades Freed',
  'author_id': '4725841',
  'author': 'E.L. James',
  'position': {'ranking': 37, 'score': 29101, 'votes': 315}},
 {'book_id': '35220',
  'title': 'The Red Badge of Courage',
  'author_id': '19879',
  'author': 'Stephen Crane',
  'position': {'ranking': 38, 'score': 29091, 'votes': 304}},
 {'book_id': '6867',
  'title': 'Atonement',
  'author_id': '2408',
  'author': 'Ian McEwan',
  'position': {'ranking': 39, 'score': 28939, 'votes': 302}},
 {'book_id': '56495',
  'title': 'The Purpose Driven Life: What on Earth Am I Here for?',
  'author_id': '711',
  'author': 'Rick Warren',
  'position': {'ranking': 40, 'score': 28210, 'votes': 305}},
 {'book_id': '3636',
  'title': 'The Giver',
  'author_id': '2493',
  'author': 'Lois Lowry',
  'position': {'ranking': 41, 'score': 28008, 'votes': 294}},
 {'book_id': '2657',
  'title': 'To Kill a Mockingbird',
  'author_id': '1825',
  'author': 'Harper Lee',
  'position': {'ranking': 42, 'score': 27173, 'votes': 288}},
 {'book_id': '703847',
  'title': 'Introduction to Scientology Ethics',
  'author_id': '33503',
  'author': 'L. Ron Hubbard',
  'position': {'ranking': 43, 'score': 26907, 'votes': 308}},
 {'book_id': '252917',
  'title': "Who's Looking Out for You?",
  'author_id': '27281',
  'author': "Bill O'Reilly",
  'position': {'ranking': 44, 'score': 26719, 'votes': 304}},
 {'book_id': '6487308',
  'title': 'Fallen',
  'author_id': '2905297',
  'author': 'Lauren Kate',
  'position': {'ranking': 45, 'score': 26398, 'votes': 277}},
 {'book_id': '13079982',
  'title': 'Fahrenheit 451',
  'author_id': '1630',
  'author': 'Ray Bradbury',
  'position': {'ranking': 46, 'score': 26072, 'votes': 274}},
 {'book_id': '7624',
  'title': 'Lord of the Flies',
  'author_id': '306',
  'author': 'William Golding',
  'position': {'ranking': 47, 'score': 25542, 'votes': 265}},
 {'book_id': '4900',
  'title': 'Heart of Darkness',
  'author_id': '3345',
  'author': 'Joseph Conrad',
  'position': {'ranking': 48, 'score': 25394, 'votes': 266}},
 {'book_id': '1656001',
  'title': 'The Host',
  'author_id': '941441',
  'author': 'Stephenie Meyer',
  'position': {'ranking': 49, 'score': 25075, 'votes': 271}},
 {'book_id': '10920',
  'title': 'Cold Mountain',
  'author_id': '7130',
  'author': 'Charles Frazier',
  'position': {'ranking': 50, 'score': 24282, 'votes': 255}},
 {'book_id': '32261',
  'title': "Tess of the D'Urbervilles",
  'author_id': '15905',
  'author': 'Thomas Hardy',
  'position': {'ranking': 51, 'score': 24229, 'votes': 256}},
 {'book_id': '6478256',
  'title': "Glenn Beck's Common Sense: The Case Against an Out-of-Control Government, Inspired by Thomas Paine",
  'author_id': '188932',
  'author': 'Glenn Beck',
  'position': {'ranking': 52, 'score': 23957, 'votes': 275}},
 {'book_id': '70401',
  'title': 'On the Road',
  'author_id': '1742',
  'author': 'Jack Kerouac',
  'position': {'ranking': 53, 'score': 22601, 'votes': 238}},
 {'book_id': '801178',
  'title': 'Chicken Soup for the Soul',
  'author_id': '35476',
  'author': 'Jack Canfield',
  'position': {'ranking': 54, 'score': 22030, 'votes': 243}},
 {'book_id': '139253',
  'title': 'The House on Mango Street',
  'author_id': '13234',
  'author': 'Sandra Cisneros',
  'position': {'ranking': 55, 'score': 21772, 'votes': 233}},
 {'book_id': '43763',
  'title': 'Interview with the Vampire',
  'author_id': '7577',
  'author': 'Anne Rice',
  'position': {'ranking': 56, 'score': 21722, 'votes': 233}},
 {'book_id': '662',
  'title': 'Atlas Shrugged',
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 {'book_id': '18943',
  'title': 'Confessions of an Ugly Stepsister',
  'author_id': '7025',
  'author': 'Gregory Maguire',
  'position': {'ranking': 951, 'score': 386, 'votes': 5}},
 {'book_id': '41667',
  'title': 'My Side of the Mountain',
  'author_id': '23509',
  'author': 'Jean Craighead George',
  'position': {'ranking': 952, 'score': 386, 'votes': 4}},
 {'book_id': '13497818',
  'title': 'The Casual Vacancy',
  'author_id': '1077326',
  'author': 'J.K. Rowling',
  'position': {'ranking': 953, 'score': 386, 'votes': 4}},
 {'book_id': '5168',
  'title': 'Where the Heart Is',
  'author_id': '3510',
  'author': 'Billie Letts',
  'position': {'ranking': 954, 'score': 384, 'votes': 4}},
 {'book_id': '13262783',
  'title': 'Every Day',
  'author_id': '11664',
  'author': 'David Levithan',
  'position': {'ranking': 955, 'score': 384, 'votes': 4}},
 {'book_id': '28866',
  'title': 'Dark Prince',
  'author_id': '6268',
  'author': 'Christine Feehan',
  'position': {'ranking': 956, 'score': 384, 'votes': 4}},
 {'book_id': '5171894',
  'title': 'The Doomsday Key',
  'author_id': '38809',
  'author': 'James Rollins',
  'position': {'ranking': 957, 'score': 384, 'votes': 4}},
 {'book_id': '7619292',
  'title': 'Twilight: The Graphic Novel, Vol. 1',
  'author_id': '4379470',
  'author': 'Young Kim',
  'position': {'ranking': 958, 'score': 383, 'votes': 5}},
 {'book_id': '5797',
  'title': 'Vanity Fair',
  'author_id': '3953',
  'author': 'William Makepeace Thackeray',
  'position': {'ranking': 959, 'score': 382, 'votes': 4}},
 {'book_id': '50840',
  'title': "Farnham's Freehold",
  'author_id': '205',
  'author': 'Robert A. Heinlein',
  'position': {'ranking': 960, 'score': 382, 'votes': 5}},
 {'book_id': '38913',
  'title': 'Follow Your Heart',
  'author_id': '21930',
  'author': 'Susanna Tamaro',
  'position': {'ranking': 961, 'score': 382, 'votes': 4}},
 {'book_id': '22328',
  'title': 'Neuromancer',
  'author_id': '9226',
  'author': 'William Gibson',
  'position': {'ranking': 962, 'score': 382, 'votes': 4}},
 {'book_id': '7082',
  'title': 'Do Androids Dream of Electric Sheep?',
  'author_id': '4764',
  'author': 'Philip K. Dick',
  'position': {'ranking': 963, 'score': 381, 'votes': 4}},
 {'book_id': '5368',
  'title': 'Forever Amber',
  'author_id': '3620',
  'author': 'Kathleen Winsor',
  'position': {'ranking': 964, 'score': 380, 'votes': 4}},
 {'book_id': '228534',
  'title': 'The Weight of Water',
  'author_id': '3530',
  'author': 'Anita Shreve',
  'position': {'ranking': 965, 'score': 380, 'votes': 4}},
 {'book_id': '56759',
  'title': 'The Mayor of Casterbridge',
  'author_id': '15905',
  'author': 'Thomas Hardy',
  'position': {'ranking': 966, 'score': 380, 'votes': 5}},
 {'book_id': '10619',
  'title': 'Rose Madder',
  'author_id': '3389',
  'author': 'Stephen King',
  'position': {'ranking': 967, 'score': 380, 'votes': 4}},
 {'book_id': '33600',
  'title': 'Shantaram',
  'author_id': '18907',
  'author': 'Gregory David Roberts',
  'position': {'ranking': 968, 'score': 380, 'votes': 4}},
 {'book_id': '257837',
  'title': 'Shane',
  'author_id': '150701',
  'author': 'Jack Schaefer',
  'position': {'ranking': 969, 'score': 379, 'votes': 5}},
 {'book_id': '22695',
  'title': 'Summer Sisters',
  'author_id': '12942',
  'author': 'Judy Blume',
  'position': {'ranking': 970, 'score': 379, 'votes': 4}},
 {'book_id': '50877',
  'title': 'The Number of the Beast',
  'author_id': '205',
  'author': 'Robert A. Heinlein',
  'position': {'ranking': 971, 'score': 379, 'votes': 4}},
 {'book_id': '10941624',
  'title': 'Ethereal',
  'author_id': '4096668',
  'author': 'Addison Moore',
  'position': {'ranking': 972, 'score': 379, 'votes': 4}},
 {'book_id': '7864437',
  'title': 'The Death Cure',
  'author_id': '348878',
  'author': 'James Dashner',
  'position': {'ranking': 973, 'score': 379, 'votes': 4}},
 {'book_id': '830',
  'title': 'Snow Crash',
  'author_id': '545',
  'author': 'Neal Stephenson',
  'position': {'ranking': 974, 'score': 378, 'votes': 4}},
 {'book_id': '11408650',
  'title': 'The Unbecoming of Mara Dyer',
  'author_id': '4126827',
  'author': 'Michelle Hodkin',
  'position': {'ranking': 975, 'score': 378, 'votes': 4}},
 {'book_id': '5489684',
  'title': 'Vampire Kisses: The Beginning',
  'author_id': '153734',
  'author': 'Ellen Schreiber',
  'position': {'ranking': 976, 'score': 377, 'votes': 5}},
 {'book_id': '77507',
  'title': 'Red Mars',
  'author_id': '1858',
  'author': 'Kim Stanley Robinson',
  'position': {'ranking': 977, 'score': 376, 'votes': 4}},
 {'book_id': '246245',
  'title': 'The Deerslayer',
  'author_id': '9121',
  'author': 'James Fenimore Cooper',
  'position': {'ranking': 978, 'score': 376, 'votes': 4}},
 {'book_id': '11590',
  'title': "'Salem's Lot",
  'author_id': '3389',
  'author': 'Stephen King',
  'position': {'ranking': 979, 'score': 376, 'votes': 5}},
 {'book_id': '34497',
  'title': 'The Color of Magic',
  'author_id': '1654',
  'author': 'Terry Pratchett',
  'position': {'ranking': 980, 'score': 376, 'votes': 4}},
 {'book_id': '46544',
  'title': 'The Shelters of Stone',
  'author_id': '861',
  'author': 'Jean M. Auel',
  'position': {'ranking': 981, 'score': 375, 'votes': 5}},
 {'book_id': '601745',
  'title': 'Making Contact with the Other Side: How to Enchance Your Own Psychic Powers',
  'author_id': '4333',
  'author': 'Sylvia Browne',
  'position': {'ranking': 982, 'score': 375, 'votes': 8}},
 {'book_id': '44184',
  'title': 'Monster',
  'author_id': '13291',
  'author': 'Walter Dean Myers',
  'position': {'ranking': 983, 'score': 374, 'votes': 4}},
 {'book_id': '28186',
  'title': 'The Sea of Monsters',
  'author_id': '15872',
  'author': 'Rick Riordan',
  'position': {'ranking': 984, 'score': 374, 'votes': 4}},
 {'book_id': '469571',
  'title': 'All the Pretty Horses',
  'author_id': '4178',
  'author': 'Cormac McCarthy',
  'position': {'ranking': 985, 'score': 374, 'votes': 4}},
 {'book_id': '79379',
  'title': 'Violets Are Blue',
  'author_id': '3780',
  'author': 'James Patterson',
  'position': {'ranking': 986, 'score': 373, 'votes': 6}},
 {'book_id': '15924',
  'title': 'At First Sight',
  'author_id': '2345',
  'author': 'Nicholas Sparks',
  'position': {'ranking': 987, 'score': 373, 'votes': 4}},
 {'book_id': '6442769',
  'title': 'Paper Towns',
  'author_id': '1406384',
  'author': 'John Green',
  'position': {'ranking': 988, 'score': 373, 'votes': 5}},
 {'book_id': '86172',
  'title': 'A Man in Full',
  'author_id': '3083854',
  'author': 'Tom Wolfe',
  'position': {'ranking': 989, 'score': 372, 'votes': 6}},
 {'book_id': '28862',
  'title': 'The Prince',
  'author_id': '16201',
  'author': 'Niccolò Machiavelli',
  'position': {'ranking': 990, 'score': 372, 'votes': 5}},
 {'book_id': '554798',
  'title': 'The Official Pokemon Handbook',
  'author_id': '347488',
  'author': 'Maria S. Barbo',
  'position': {'ranking': 991, 'score': 371, 'votes': 6}},
 {'book_id': '5960207',
  'title': 'Mr. & Mrs. Fitzwilliam Darcy: Two Shall Become One',
  'author_id': '603838',
  'author': 'Sharon Lathan',
  'position': {'ranking': 992, 'score': 370, 'votes': 4}},
 {'book_id': '7673',
  'title': 'Eaters of the Dead',
  'author_id': '5194',
  'author': 'Michael Crichton',
  'position': {'ranking': 993, 'score': 369, 'votes': 5}},
 {'book_id': '18412',
  'title': 'The Wind Done Gone',
  'author_id': '11087',
  'author': 'Alice Randall',
  'position': {'ranking': 994, 'score': 369, 'votes': 4}},
 {'book_id': '4008',
  'title': 'The Devil and Miss Prym',
  'author_id': '566',
  'author': 'Paulo Coelho',
  'position': {'ranking': 995, 'score': 368, 'votes': 4}},
 {'book_id': '109513',
  'title': 'The Phantom of Manhattan',
  'author_id': '36714',
  'author': 'Frederick Forsyth',
  'position': {'ranking': 996, 'score': 368, 'votes': 4}},
 {'book_id': '6381205',
  'title': 'Soulless',
  'author_id': '2891665',
  'author': 'Gail Carriger',
  'position': {'ranking': 997, 'score': 367, 'votes': 4}},
 {'book_id': '6391',
  'title': 'Christmas in Heaven',
  'author_id': '4333',
  'author': 'Sylvia Browne',
  'position': {'ranking': 998, 'score': 366, 'votes': 6}},
 {'book_id': '117376',
  'title': 'Rush Hudson Limbaugh and His Times: Reflections on a Life Well Lived',
  'author_id': '19794',
  'author': 'Rush Limbaugh',
  'position': {'ranking': 999, 'score': 366, 'votes': 9}},
 {'book_id': '6936382',
  'title': 'Anna and the French Kiss',
  'author_id': '3095893',
  'author': 'Stephanie Perkins',
  'position': {'ranking': 1000, 'score': 365, 'votes': 4}},
 ...]

def check_book_id(book_id):
    return 1 if book_id in int_book_ids else 0

value2 = booko3.loc[0, 'books']#extract the column books from the row worst books of all time
chunksize= 10**4
chunks=[]

for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
    chunk['id'] = pd.to_numeric(chunk['id'])
    chunk['num_pages'] = pd.to_numeric(chunk['num_pages'])
    chunk = chunk.dropna(subset=['id', 'num_pages'])#drop rows, that contain an empty string either for 'id' or 'num_pages'
    chunks.append(chunk[['id', 'num_pages']])#Only keep the columns 'id' and 'num_pages'
df = pd.concat(chunks, axis=0)#create a new dataframe only containig the stuff that was kept from the chunks
book_ids = [d['book_id'] for d in value2]#Make a list of the book_ids
int_book_ids = list(map(int, book_ids))# make integers of the book_ids
df['sino'] = df['id'].apply(check_book_id)#call the function check_book_id on every element of the list and store either 1 or 0 in a new column 'sino'
filtered_df = df[df['num_pages'] > 700] # Select only the books with more than 700 pages
filtered_df2 = df[(df['num_pages'] > 700) & (df['sino'] == 1)]# select the books with more than 700 pages and are contained in the 'worst books of all time' list
prob= len(filtered_df2)/len(filtered_df)
print(prob)

0.0019798416126709864

Question 4

#Are the events X=’Being Included in The Worst Books of All Time list’ and Y=’Having more than 700 pages’ independent? Explain how you have obtained your answer.
# We will do a chi- square test on idependence to check whether they are independent or not

import json
import pandas as pd
import scipy.stats as stats
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
booko2= pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", nrows=10, lines= True)
booko3=pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/archive/list.json/list.json", nrows=10, lines=True)

#var1= Being included in the Worst Books of All Time list, ##code extracted from 7.3
value2 = booko3.loc[0, 'books']
def check_book_id(book_id):
    return 1 if book_id in int_book_ids else 0
chunksize= 10**4
chunks=[]

for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
    chunk['id'] = pd.to_numeric(chunk['id'])
    chunk['num_pages'] = pd.to_numeric(chunk['num_pages'])
    chunk = chunk.dropna(subset=['id', 'num_pages'])
    chunks.append(chunk[['id', 'num_pages']])
df = pd.concat(chunks, axis=0)
book_ids = [d['book_id'] for d in value2]
int_book_ids = list(map(int, book_ids))
df['sino'] = df['id'].apply(check_book_id)

#var2= Having more than 700 pages 
def check_700(num_pages):
    return 1 if num_pages>700 else 0
df['si700'] = df['num_pages'].apply(check_700)# calls function for every row on the column 'num_pages' and stores either 0 or one in the new column 'si700'

contingency_table = pd.crosstab(df['sino'], df['si700'])

chi2, p, dof, expected = stats.chi2_contingency(contingency_table)

print(p)

3.092149285282895e-06

#As the result is smaller than 0.05 we can conclude that the two variables are dependent

[RQ8] Charts, statistical tests, and analysis methods are splendid tools to illustrate your data-driven decisions to check whether a hypothesis is correct.

Question 1

import json
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
import numpy as np

chunksize = 10 ** 4  
chunks = []

#chunking and data cleaning
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
    chunk['average_rating'].replace('', np.nan, inplace=True)
    chunk['num_pages'].replace('', np.nan, inplace=True)
    chunk['average_rating'].replace(0.00, np.nan, inplace=True)
    chunk['num_pages'].replace(0, np.nan, inplace=True)
    chunk['average_rating'] = pd.to_numeric(chunk['average_rating'])
    chunk['num_pages'] = pd.to_numeric(chunk['num_pages'])
    chunk = chunk.dropna(subset=['average_rating', 'num_pages'])
    chunks.append(chunk[['average_rating', 'num_pages']])

#creating a dataframe    
df = pd.concat(chunks, axis=0)

correlation = df['average_rating'].corr(df['num_pages'])
print(correlation)

-0.00031640662915722207

The coefficient is slightly smaller than 0, indicating that there is no correlation between the length of a book and the rating.The longest books are not usually rated the worst. As the correlation is even negative, it would rather be the opposite.

Question 2

import json
import pandas as pd
from scipy.stats import ttest_ind
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
import matplotlib.pyplot as plt
import numpy as np

chunks=[]
chunksize=10**4
nrows = 10**3

#chunking and data cleaning
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_books.json", chunksize=chunksize, lines=True):
    chunk = chunk[['average_rating', 'language']]
    chunk['language'].replace('', np.nan, inplace=True)
    chunk['average_rating'].replace('', np.nan, inplace=True)
    chunk['average_rating'].replace(0.00, np.nan, inplace=True)
    chunk.dropna(subset=['language'], inplace=True)
    chunk.dropna(subset=['average_rating'], inplace=True)
    chunk['average_rating']= pd.to_numeric(chunk['average_rating'])
    chunks.append(chunk)

#Creating dataframe
chunks = pd.concat(chunks, axis=0)

#Creting a new column that is 1 for english books and 0 for nonenglish books
chunks['is_english']= chunks['language'].apply(lambda x: int( x[:3] in ['en','eng',"en-"]))

#Create groups for t-test and doing t-test
english_books= chunks[chunks['is_english'] ==1]
non_english_books= chunks[chunks['is_english'] ==0]
t_stat, p_val = ttest_ind(english_books['average_rating'], non_english_books['average_rating'])

print(p_val)

0.0

The p-value is very low, lower than the often used significance value of 0.05. This means, that the average rate distribution of english and non-english books isn't siginificantly different

To further illustrate this we also plotted the average rate distribution for english and nonenglish books in histograms

# Histogram for english books
plt.hist(english_books['average_rating'], alpha=0.8, label='English')

(array([  2587.,    833.,   6952.,   7825.,  18804., 128658., 381247.,
        599300., 229201.,  81415.]),
 array([1. , 1.4, 1.8, 2.2, 2.6, 3. , 3.4, 3.8, 4.2, 4.6, 5. ]),
 <BarContainer object of 10 artists>)

# Histogram for non-english books
plt.hist(non_english_books['average_rating'], alpha=0.5, label='Non_English')

(array([  1897.,    715.,   6859.,   8003.,  18997., 115380., 302100.,
        452833., 159666.,  36380.]),
 array([1. , 1.4, 1.8, 2.2, 2.6, 3. , 3.4, 3.8, 4.2, 4.6, 5. ]),
 <BarContainer object of 10 artists>)

The two Histograms illustrate that there is no significant difference in the average rate distribution of english and non-english books

Question 3

#Defining variables for the boxplot
ratings_english = english_books['average_rating'].tolist()
ratings_non_english = non_english_books['average_rating'].tolist()

#Creating the boxplot
plt.boxplot([ratings_english, ratings_non_english], labels=['english', 'non-english'])
plt.title('Comparison of average rates')
plt.ylabel('Rate')
plt.show()

#Calculating the means
mean_english = english_books['average_rating'].mean()
mean_non_english = non_english_books['average_rating'].mean()
print('Mean english books: %.3f' % mean_english)
print('Mean non-english books: %.3f' % mean_non_english)

Mean english books: 3.895
Mean non-english books: 3.839

The two means are really close to each other. The mean isn't shown in a boxplot. If the data is perfectly symmetric, the mean is identical with the median

#Calculating the median
median_english = english_books['average_rating'].median()
median_non_english = non_english_books['average_rating'].median()
print('Median english books: %.3f' % median_english)
print('Median non-english books: %.3f' % median_non_english)

Median english books: 3.920
Median non-english books: 3.890

The medians of english and non-english books are really close to each other. The median is the yellow line in the boxplot. Half of the average rates are above the line and half below it. In a boxplot the median is important to show the skewness of the data. As the median for both english and non-english books is more or less in the middle of the box, we can conclude that are data is symmetric.

#Calculating the mode
mode_english = english_books['average_rating'].mode()
mode_non_english = non_english_books['average_rating'].mode()
print('Mode english books: %.3f' % mode_english)
print('Mode non-english books: %.3f' % mode_non_english)

Mode english books: 4.000
Mode non-english books: 4.000

The mode isn't shown in a boxplot, but if the boxplot is perfectly symmetric it is identical with the mean and average.

#Calculating the quartiles
q1_english = english_books['average_rating'].quantile(0.25)
q2_english = english_books['average_rating'].quantile(0.5)
q3_english = english_books['average_rating'].quantile(0.75)

q1_non_english = non_english_books['average_rating'].quantile(0.25)
q2_non_english = non_english_books['average_rating'].quantile(0.5)
q3_non_english = non_english_books['average_rating'].quantile(0.75)

print('Q1 english books: %.3f' % q1_english)
print('Q2 english books: %.3f' % q2_english)
print('Q3 english books: %.3f' % q3_english)
print('Q1 non-english books: %.3f' % q1_non_english)
print('Q2 non-english books: %.3f' % q2_non_english)
print('Q3 non-english books: %.3f' % q3_non_english)

Q1 english books: 3.670
Q2 english books: 3.920
Q3 english books: 4.150
Q1 non-english books: 3.620
Q2 non-english books: 3.890
Q3 non-english books: 4.110

For both english and non-english books, the interquartile range(Q3-Q1) is quite small. This means that our data isn't really dispersed. The interqaurtile range is visualized by the length of the boxplot.

Question 4

import json
import pandas as pd
import statsmodels.api as sm
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import pearsonr

chunksize=10**4
chunks=[]

#chunking and data cleaning
for chunk in pd.read_json("/Users/damianzeller/Desktop/HS23/ADM/Homework 2/lighter_authors.json", chunksize=chunksize, lines=True):
    chunk = chunk[['fans_count', 'text_reviews_count']]
    chunk['text_reviews_count'].replace('', np.nan, inplace=True)
    chunk['fans_count'].replace('', np.nan, inplace=True)
    chunk.dropna(subset=['text_reviews_count'], inplace=True)
    chunk.dropna(subset=['fans_count'], inplace=True)
    chunk['text_reviews_count']= pd.to_numeric(chunk['text_reviews_count'])
    chunk['fans_count']= pd.to_numeric(chunk['fans_count'])
    chunks.append(chunk)

#Creating a new dataframe
chunks = pd.concat(chunks, axis=0)

#Creating variables for the Pearsons Correlation
fans = chunks['fans_count']
reviews = chunks['text_reviews_count']

#Calculating the Pearsons Correlation
correlation, _ = pearsonr(fans, reviews)
print('Pearsons correlation: %.3f' % correlation)

Pearsons correlation: 0.694

The coefficient of 0.694 indicates a positive correlation. The more fans you have, the more reviews you will get.

Question 5

Hypothesis testing is usually done by formulating a null hypothesis, which states that their either is a certain relationship between variables or not. In a second step the prediction of the hypothesis is tested by observing data, which leads to a rejection or acceptance of the null hypothesis. The tests used for hypothesis testing can be divded in two groups: Parametric and nonparametric tests. The main difference between these kind of tests is that parametric tests make certain assumptions about the data (e.g. normally distributed, same variance, sampled randomly), while nonparametric tests don't do that and are more factual. Further for parametric tests the sample size needs to be bigger. We chose parametric tests as they can be computed and interpreted easier than nonparametric tests and we didn't see any of the assumptions about the data as violated.

Bonus Part

1.

Select one alternative library to Pandas (i.e., Dask, Polar, Vaex, Datatable etc.), upload authors.json dataset, and filter authors with at least 100 reviews. Do the same using Pandas and compare performance in terms of milliseconds.

!pip install dask

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Requirement already satisfied: importlib-metadata>=4.13.0 in /usr/local/lib/python3.10/dist-packages (from dask) (6.8.0)
Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata>=4.13.0->dask) (3.17.0)
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# Load data using Pandas
start_time = time.time()
pandas_df = pd.read_json(authors_set, lines=True)


# Filter authors with at least 100 reviews
author_counts = pandas_df['name'].value_counts()
authors_with_100_reviews = author_counts[author_counts >= 100].index
filtered_pandas = pandas_df[pandas_df['name'].isin(authors_with_100_reviews)]

pandas_time = (time.time() - start_time) * 1000  # Convert to milliseconds

print("Pandas time (ms):", pandas_time)

Pandas time (ms): 24993.821382522583

import dask.dataframe as dd
import dask

# Load data using Dask
start_time = time.time()
dask_df = dd.read_json(authors_set,lines=True)

# Filter authors with at least 100 reviews
author_counts = dask_df['name'].value_counts()
authors_with_100_reviews = author_counts[author_counts >= 100].compute()
filtered_dask = dask_df[dask_df['name'].isin(authors_with_100_reviews)]

dask_time = (time.time() - start_time) * 1000  # Convert to milliseconds

print("Dask time (ms):", dask_time)

Dask time (ms): 36796.88239097595

As we can see that implementing the task with pandas takes less time than its alternative called DASK. The direct implementation same as pandas gives the above result, though the dask provides the distributed computing services so as to divide the work into number of workers , the later might work effectively interms of time complexity.

Command Line Question:

Command Line Original Script:

#!/bin/bash
echo "id|title|total_books_count"
jq -r '. as $parent | .works[] | [$parent.id, $parent.title, .books_count] | join("|")' series.json | awk -F'|' '{a[$1"|"$2]+=$3} END{for (i in a) print i"| "a[i]}' | sort -t'|' -k3nr | head -5

Output of Original Script:

Command Line LLM Script:

#!/bin/bash
echo "id|title|total_books_count"
jq -r '. as $parent | .works[] | [$parent.id, $parent.title, .books_count] | join("|")' series.json | awk -F'|' '{a[$1"|"$2]+=$3} END{for (i in a) print i"| "a[i]}' | sort -t'|' -k3nr | head -5

Interaction with LLM Chatbot tools;

Prompt Used : Considering the following shell script command which is for reporting the title of the top 5 series with the highest total 'books_count' among all of their associated books. Can you please implement the more robust solution for it ?

---> Upon implementation the above solution was given based on the fact that the robustness is defined on various factors, including code readability, ease of maintenance, and specific project requirements. Also one different solution was given which handles error and exception if the input file is not present but it was more than three lines of script.

AWS Question (AWSQ)

from google.colab import drive
drive.mount('/content/drive')
%cd /content/drive/MyDrive/HW2

Mounted at /content/drive
/content/drive/MyDrive/HW2

import pandas as pd
import time
#we store the start time of the script.
start_time= time.time()
#we initialise an empty list
tags_list = []
# we take a chunk size
chunk_size = 20000
# we initialize an empty list to store chunks
lists = pd.DataFrame()
# We Loop through each chunk and append it to the result dataframe
with open('list.json', 'r') as lists_set:
  for chunk in pd.read_json(lists_set, lines=True, chunksize=chunk_size):
        # We have to Flatten the lists of tags and extend the tags_list
        for tags in chunk['tags']:
            if isinstance(tags, list):
                tags_list.extend(tags)
tags_df = pd.DataFrame({'tags': tags_list})
tags_df.dropna(inplace=True)
# We now will count the usage of each tag
tag_counts = tags_df['tags'].value_counts().reset_index()
tag_counts.columns = ['tag', '#usage']
# We will Sort the DataFrame by usage count in descending order
sorted_tags = tag_counts.sort_values(by='#usage', ascending=False)

end_time= time.time()
# then we print the top tags and time taken
print(sorted_tags.head(5))
print(f"Time taken: {end_time - start_time:.2f} seconds")

               tag  #usage
0          romance    6001
1          fiction    5291
2      young-adult    5016
3          fantasy    3666
4  science-fiction    2779
Time taken: 74.91 seconds

I have used this as a script file in the name of aws_solution.py and have run the script from the command line. This is the attached screenshot below:

As evident from the screenshot, the result came as expected and took 53.34 seconds in my own macbook.

Then I have created an AWS EC2 instance with the following specifications:

t3.large, volume=30giB

Then I copied the AWS folder containing the necessary files from my system to EC2 instance after connecting to it from the command line as in the following screenshots:

Then I run the script commands in the aws ubuntu:

In the EC2 ubuntu, it took 57.29 seconds to run the same script while it took 53.34 seconds in my own macbook.

Algorithm Question

from collections import deque

# Read the number of instructions
num_instructions = int(input())

# Initialize a deque to represent the bookshelf
bookshelf = deque()

# Process each instruction
for _ in range(num_instructions):
    instruction = input().split()
    action, book_id = instruction[0], int(instruction[1])

    if action == 'L':
        # Place the book to the left of the leftmost existing book
        bookshelf.appendleft(book_id)
    elif action == 'R':
        # Place the book to the right of the rightmost existing book
        bookshelf.append(book_id)
    elif action == '?':
        # Calculate the minimum number of books to pop from both sides
        left_count = bookshelf.index(book_id)
        right_count = len(bookshelf) - left_count - 1
        # Print the result
        print(min(left_count, right_count))

8
L 75
R 20
R 30
L 11
? 75
1
L 12
L 15
? 20
1

2---> According to LLM Chatbot tool :

To analyze the time complexity of the provided code, we can break it down into its main operations:

Looping through the boss's instructions: This operation takes O(n) time, where 'n' is the number of instructions. For each instruction, we perform the following operations: For 'L' or 'R' instructions, we append to the deque, which takes O(1) time. For '?' instructions, we use the index method to find the position of the book, which takes O(k) time, where 'k' is the position of the book in the deque. In the worst case, 'k' could be equal to the length of the deque, making it O(n). Printing the result in each '?' instruction takes O(1) time.

Given these considerations, the overall time complexity of the code is O(n^2) in the worst case, as the worst-case scenario occurs when each '?' instruction has to search through the entire deque, and there are 'n' such instructions. '''

'''We believe the instructions given by the LLM Chatbot tool is correct and upon observation with different input sizes we can see that the most expensive operation in the code is to calculate the ? instructions.'''

3 ---> NO the code provided above is not the optimal code , we can reduce the time complexity of the above code by using a different data structure called dictionary. The time complexity for it can be reduced to O(n)

Algorithm:

Initialize an empty dictionary called book_positions

Initialize an empty list called bookshelf

Read num_instructions

For i in range(num_instructions): Parse the instruction into action and book_id

If action is 'L':
    Insert book_id at the beginning of bookshelf
    Store the position of book_id in book_positions

If action is 'R':
    Append book_id to the end of bookshelf
    Store the position of book_id in book_positions

If action is '?':
    Retrieve book_id's position from book_positions
    Calculate left_count as min(book_id's position, length of bookshelf - book_id's position - 1)
    Print left_count

efficient O(1) time complexity for the '?' instructions.